Program

Type: presentation, 45 min Language: en Tags: ML Audience: Beginner

Abstract:

The advent of machine learning along with its integration with big data has enabled users to efficiently to develop solutions for innumerable use cases. A machine learning model consists of an algorithm which draws some meaningful correlation between the data without being tightly coupled to a specific set of rules. It's crucial to explain the subtle nuances of the network along with the use-case we are trying to solve. With the advent of technology, the quantity of data has increased which in turn has increased the need for resources to process the data while building a model. The main question, however, is to discuss the need to develop lightweight models keeping the performance of the system intact. To connect the dots, we will talk about the development of these applications specifically aimed to provide equally accurate results without using much of the resources. This is achieved by using image processing techniques along with optimizing the network architecture.

Speaker(s):

Akshay Bahadur

Akshay Bahadur's interest towards computer science sparked when he was working on a women's safety application aimed towards the women welfare in India and since then he has been incessantly working on improving my skills. He has made successful prototypes like autonomous car, alphabet recognition, cancer classification, gesture recognition using learning models. His ambition is to make valuable contribution towards ML community and leave a message of perseverance and tenacity. Currently, he is working as a software engineer at Symantec, India. He's is one out of 8 Google Developer Expert (Machine Learning) from India along with being one of 150 members worldwide for Intel Software Innovator program. His recent contribution on developing an Indian Sign Language Recognition (ISLAR) has been appreciated worldwide.

Type: short talk, 30 min Language: en Tags: Cloud Audience: Beginner

Abstract:

The cloud is a magic place. Your product teams create wonderful services; publish them for the world to see and then realize that this magic place has some very different rules.

This session will show a real-world story of how Vipps moved its traditional ops gradually to cloud-native in Azure. There will be some non-technical discussions about various Azure services.

This talk is for IT decision makers like architects, leaders but also agile coaches that can help the development teams to move to the cloud.

It is assumed that you understand the basic concept of the cloud, some technical understanding, and the wish of moving to Azure.

Speaker(s):

Sven Malvik

Sven is the leader of the platform team at Vipps. His job is to ensure that Vipps builds a solid, secure, and flexible foundation in Azure that the developers want to use. He has spoken at conferences like Microsoft Build, Javazone and various Meetup groups.

Type: short talk, 30 min Language: en Tags: AI, Data Science, Ethics Audience: Beginner

Abstract:

Over the years, businesses have come to realize that to have amazing growth and profitability using AI, it usually boils down to delivering great customer experiences. What if there was a way to enhancing the reach and scale of your human staff using AI such that you could augment, not automate? So that you could retain, not replace the expertise of your business users? My talk is about a unique slant of AI called human-centred AI, along with a playbook for architecting ML systems using microservices that has worked exceptionally well for some problems in retail.

Speaker(s):

Vivek Bharadwaj

I am a full-stack Data Scientist with over 12 years of experience in analytics and machine learning. Currently, I work for Australia's largest fashion e-commerce company called THE ICONIC and lead their marketing science function, where I have built machine learning models for churn, lifetime value and multi-channel attribution as well as mapped out customer journey events.

Type: presentation, 45 min Language: no Tags: Cloud, ML, Research Audience: Intermediate

Abstract:

I denne sesjonen skal vi snakke om dyp læring for segmentering av barnehjerter. Vi bruker state of the art nevrale nett for å segmentere hjerter med medfødt feil, hvor målet er å framstille hjertene i 3D for bedre operasjonsplanlegging. Vi skal gå igjennom arkitekturen vi bruker, teknologien bak, utfordringer og tips når man jobber med 3D bildedata.

Speaker(s):

Brede Bjørhovd

Brede is a senior data scientist at Sopra Steria, while there he has worked on mostly deep learning projects, ranging from automated design to customer segmentation. He has also worked in a computer vision start-up in Bergen.

Snorre Alm Harestad

Snorre Alm Harestad is an Oslo-based developer and data scientist with almost five years experience building business-critical, intelligent and cloud-based solutions for large Norwegian enterprises. He is currently working on an inter-disciplinary project together with clinicians attempting to automate medical image segmentation of organs for surgery planning and navigation. His role consists of developing architecture and infrastructure for training AI models utilising machine learning techniques such as neural networks, as well as the solution itself based on top of TensorFlow.

Type: short talk, 30 min Language: En Tags: AI, Data Science, ML, Research Audience: All

Abstract:

The language model BERT is a huge break-through in NLP, published in 2018 by Google, with both trained models and code available under an extremely unrestrictive license. The models even support Norwegian Bokmål and Nynorsk, as well as several other low-resource languages.

This opens up new and exciting possibilities for ordinary companies without the resources of Google and Facebook, both in terms of computing power and datasets. What are these possibilities?

Speaker(s):

Sigrid L. Bjørndal

Sigrid L. Bjørndal is an Oslo-based data scientist and developer, who recently graduated from NTNU with a master in Machine Learning. She wrote her master thesis on applying recent developments in Natural Language Processing, including BERT, to a practical application for a large Norwegian bank. She is currently working for Sopra Steria together with clinicians on an inter-disciplinary project, where she is using AI to automate medical image segmentation of organs, with the goal of improving complex surgery planning and navigation.

Type: workshop, 90 min Language: En Tags: AI, Ethics, Fairness in ML, Research Audience: Intermediate

Abstract:

During this workshop we'll teach you what you have to know to account for fairness when building machine learning pipelines. The first hour will set the theorethical background necessary for the second hands-on part. Audience: Basic ML knowledge is required. We assume you know how to work with data and train a simple ML model. Basic math undertanding of probability.

Speaker(s):

Marco Bertani-Økland

Mathematician and software engineer who cares about building a sustainable future with technology. Working on Responsible AI in both industry and academy.

Josephine Honoré

Josephine Honoré er M.Sc. i Software Development og jobber som kunnskapsingeniør i Computas. Hun har skrevet masteropgave omkring fair anbefalingssystemer og interesserer sig særligt for temaer inden for retfærdig, ansvarlig og forklarbar maskinlæring.

Type: Short talk, 30 min Language: En Tags: Data Science, ML, Open standards Audience: Intermediate

Abstract:

The use of Machine Learning in all application areas is on the rise. Once a good model is created, it needs to be serialized to be transmitted and deployed, i.e. positioned for producing predictions for new cases. This is often difficult because model building and deployment are typically done by different teams, using different programming environments and languages. In this talk we will explain open standards (PMML, PFA, ONNX) that have made model exchange and deployment easier and show how they are or can be used in some applications, including healthcare.

Speaker(s):

Svetlana Levitan

Svetlana is a Senior Developer Advocate at IBM. She works on PMML and ONNX, open standards for ML model deployment. Svetlana presents workshops, conference talks, meetups around the world.

Type: Short talk, 30 min Language: En Tags: AI, ML, Cloud Audience: Intermediate

Abstract:

This talk will be both introduction to Generative Adversarial Networks, and to Azure Machine Learning. I will use GAN as an example to show how convenient it is to perform computationally intensive neural network training on Azure Machine Learning, and discuss what advantages it gives to the Data Scientist.

Speaker(s):

Dmitry Soshnikov

Cloud Developer Advocate at Microsoft, Associate Professor at MIPT, HSE and MAI, Amateur Digital Artist, Father and Geek.

Type: Short talk, 30 min Language: En Tags: AI, ML Audience: Beginner

Abstract:

On-Device Machine Learning will explore ways to train and run a Deep Learning Model on your edge devices such as Smartphones, IoT Devices and devices without an OS like Microcontroller units (MCU). This presentation will explore next generation techniques to run a Machine Learning model that can be power efficient, respect Data privacy and security, and computationally efficient without losing any performance.

Speaker(s):

Kshitiz Rimal

Kshitiz Rimal is an AI Developer from Nepal. He is Google Developers Expert (GDE) on Machine Learning, Intel AI Student Ambassador and currently a co-founder and Head of Research at Artificial Intelligence for Development, a not-for-profit research organization in Nepal.
For the past 8 years he has been developing software and recently, for the past 3 years he is involved with Deep Learning. He is one of the founding members of the first community on Deep Learning established in Nepal. He has been developing projects around Deep Learning, delivering hands-on workshops on that particular technology, organizing meetups, presenting at international conferences and delivering AI training all around the world, which includes, USA, Singapore, China, Switzerland, Sweden and many others.
He is a 1st-runner up winner in a competition on Disaster relief and response, called "Call for Code 2018", for his project PD3R, which was on Structural Retrofitting using AI. He recently delivered a demo presentation and co-instructed a hands-on workshop at AI for Good Global Summit 2019, in Geneva, for his project called Cash Recognition for Visually Impaired, which is under the theme of AI for Accessibility. He is passionate about AI and working actively how it can be used for the good of mankind.

Type: Short talk, 30 min Language: En Tags: Cloud, Data Science Audience: Intermediate

Abstract:

Building analytics pipelines that can ingest data at a scale is not a simple task. However in this session I want to show you how you can build a serverless analytics pipeline using different serverless components and 0 code.

This pipeline is design to scale and to be highly available and will be hosted in the cloud. This is a very hands on session where we are going to use different services like: Kinesis Firehose, AWS Glue, AWS Athena and Quicksight.

Speaker(s):

Marcia Villalba

Marcia is a developer advocate for AWS and the host of FooBar a youtube channel (https://bit.ly/foobar-youtube) where she publishes content every week, related to serverless and the cloud.

Type: Short talk, 30 min Language: En Tags: AI, Ethics, ML Audience: Intermediate

Abstract:

Research have shown that emotions play an integral role in decision making, cognition, perception, learning and more. If we want our computers to be intelligent and be able to interact with us we need to ensure that they are able to recognize, understand and express emotions. This is the basic assumption of the field of Affective Computing. In this talk I will give an overview of Affective computing and how it can be applied in order to make our interaction with machines more suitable to us as humans.

First, I will give an introduction to the field starting with established findings from the field of psychology on how we best can measure emotions.

Then, I will describe how the field of Affective Computing has transformed from its origin in the 90’s until now when it is an established research field. I will highlight some of the technology enablers that has made Affective Computing a hot topic nowadays and give some examples of API and services that we as developers can use as of today.

In the second part of my talk, I will give some examples on application scenarios across various fields (retail, medical, education and social). After that I will be show casing what is in the front line now. I will conclude my presentation with some recommendations on how this affects us as developers going forward.

Speaker(s):

Håkan Silfvernagel

Håkan is working as Manager AI and Big Data at Miles AS.

He is active as Chairman of the Norwegian .NET User Group Oslo and as an Ambassador for Oslo.AI.

Håkan is also a Microsoft AI MVP.

Type: Short talk, 30 min Language: En Tags: AI, Data Science, ML Audience: Intermediate

Abstract:

What is deep learning? How does it work and where can it be used?

In this presentation we will talk about the problems related to deep learning and the improvements that has made it an interesting option for machine learning.

We will talk about convolutional neural networks and learn how they work.

Speaker(s):

Heli Helskyaho

Heli Helskyaho is the CEO for Miracle Finland Oy. Heli holds a Master’s degree (Computer Science) at the University of Helsinki and she is specialized on databases. At the moment she is working on her doctoral studies, researching and teaching at the University of Helsinki. Heli has been working on IT since 1990. Heli is an Oracle ACE Director, an Oracle Groundbreaker Ambassador, and a frequent speaker in many conferences. She is the author of Oracle SQL Developer Data Modeler for Database Design Mastery (Oracle Press 2015) and a co-author of Real World SQL and PL/SQL: Advice from the Experts (Oracle Press 2016).

Heli was listed as one of the TOP 100 influences on IT sector in Finland in 2015, in 2016, in 2017, in 2018, and again in 2019.

Type: Presentation, 45 min Language: En Tags: AI, ML Audience: Beginner

Abstract:

Machine Learning is Beautiful, especially in the JavaScript. Watch as we use JS to explore AI on the edge. That means plugins, mobile and even the browser! Let's explore it together!

Speaker(s):

Gant G Laborde

Gant Laborde is an owner of Infinite Red, mentor, adjunct professor, published author, and award-winning speaker. Follow Gant’s adventures at https://gantlaborde.com/.

Gant is a GDE in Web/ML, Cloudinary MDE, and Oracle Groundbreaker Ambassador.

Type: Presentation, 45 min Language: En Tags: Cloud, Data Science, ML Audience: Intermediate

Abstract:

One of the hottest topics in database land these days is BigQuery ML. A new way to use machine learning on top of tabular data straight on your tables without leaving the query editor.

With BigQuery ML, you can build machine learning models without leaving the database environment and training it on massive datasets.

In this demo session, we are going to demonstrate common marketing Machine Learning use cases how to build, train, eval and predict, your own scalable machine learning models using SQL language.

The audience will get first hand experience how to write CREATE MODEL sql syntax to build machine learning models such as:
- Multiclass logistic regression for classification
- K-means clustering
- Import TensorFlow models for prediction in BigQuery

Models are trained and accessed in BigQuery using SQL — a language data analysts know. This enables business decision making through predictive analytics across the organization without leaving the query editor

Speaker(s):

Marton Kodok

Márton is a Google Developer Expert(GDE) senior software architect at REEA.net. A romanian hero on StackOverflow with 172k reputation points. He led the implementation of complex and distributed systems serving millions of users for companies like FreeLogoServices, LogoMix, WaterSmart, Ausschreibungsdienste and many more.

Active contributor for open-source solutions like Beanstalkd console, and Riak admin interface. Expert in databases and systems like Google BigQuery, Elasticsearch, Redis.

Type: Short talk, 30 min Language: En Tags: AI, Data Science, ML Audience: Advanced

Abstract:

Three things are certain in life: death, taxes, and the fact that gradient boosting is awesome. XGBoost, LightGBM or CatBoost; there is a flavor of boosting for everyone, and they all get the job done whether you're competing on Kaggle or solving problems in your day job. 

At Kolonial.no - Norways largest online grocery player by name and tech/logistics company by trade - we use boosting models for forecasting and a couple of other areas, to make sure we keep delivering on our promise to create freedom and flow in our customers' daily lives. We have built a set of tools around common (and not so common!) machine learning pipeline functionality for tuning, training and making predictions with boosting models, so data scientists don't have to write boilerplate code and we can get up and running with new projects and pipelines in a few days instead of weeks.

Want to know why and how boosting will solve all your problems? Do you want to be that data scientist who gets things done by simply making great pipelines with just the right amount of feature engineering, .fit(...) and .predict(...) with the right algorithms and hyperparameters, and robust validation? This talk is for you!

Speaker(s):

Kjetil Åmdal-Sævik

Kjetil is Data Science Manager in Kolonial.no, which has been his dream job ever since he learned that ML is a thing and online groceries is a thing. He loves to backprop gradients and boost trees.

Type: Short talk, 30 min Language: En Tags: Data Science, ML, Research Audience: Advanced

Abstract:

Calculation of similarity between two entities is a key step in several data mining processes. While there are several common similarity measures for continuous data, there is little work for categorical data. Most approaches are purely data-driven and don’t consider the inherent dependencies of complex domains such as geological structures etc. We propose two new similarity measures that take into account semantic information to calculate the similarity between two categorical values. We apply our methods to a specific complex data mining task in the oil and gas industry: reservoir analogue identification.

Speaker(s):

Summaya Mumtaz

Summaya is a PhD research fellow at SIRIUS (Centre for Scalable Data Access for Oil and Gas), University of Oslo. Predictive analytics is the use of statistics, machine learning and modelling to analyze current and historical facts to make predictions about future events. However, standard machine learning techniques fail to produce quality predictions in complex domains. Currently, Summaya is working to add domain information into ML models for improved predictions.

Type: Short talk, 30 min Language: En Tags: AI, Cloud, Data Science, Ethics, ML Audience: Intermediate

Abstract:

We have heard about AI and its many applications but also it is importance to know and understand why we need multidisciplinary teams (diversity) to build AI knowledge and AI based solutions for the world, as well as understanding the importance of human-centered design for AI solutions.

This talk's aim is to share experience about AI diversity teams as well as good practices for designing.

Speaker(s):

Lesly Zerna

Gooogle Developer Expert in Machine Learning, co founder Mentor Her project to encourage girls to join tech careers. Mentor at Udacity's nanodegree of Business Analytics. International speaker. TEDx speaker 2018. Blogger at medium.com/@leslysandra about trips and tech. Instructor and professor at Catholic University in Bolivia. Ambassador and coordinator for City.AI in latino america. Currently, leading the innovation, research and dev department at the e-gov agency of Bolivia.

Type: Presentation, 45 min Language: En Tags: AI, Cloud, Ethics, ML, Privacy Audience: Beginner

Abstract:

Edge computing helps to break beyond the limitations imposed by, now, traditional cloud solutions. Some of the reasons might be privacy concerns, reducing the need for heavy processing resources, reducing the amount of data that is sent over the network – just to mention a few.

In this talk, we will introduce the concept and benefits of Edge Computing, how such devices can be built using affordable hardware and we will look at examples on how IoT Edge devices are in practice as well as comparing Edge Computing with other options.

As a live demo, we will be using a system built using Google Coral IoT Edge device. This is an example to process video streams on the Edge and designed to keep the privacy of the people intact; without leaking faces and identity of the people to a 3rd party. In addition to standard video processing, we will show advanced ML techniques and models that are processed on to the device to demonstrate the power and flexibility of the Edge devices nowadays.

Speaker(s):

Rustam Mehmandarov

Passionate computer scientist. Java Champion and Google Developers Expert for Cloud. Public speaker. Ex-leader of JavaZone and Norwegian JUG – javaBin.

Tannaz N. Roshandel

Tannaz works as a head engineer at the University of Oslo, where she is building an open source cloud service for the research and education sector in Norway. She has a background in robotics and is passionate about computer ethics.

Type: Short talk, 30 min Language: En Tags: Data Science, User research, UX, Business Audience: Intermediate

Abstract:

Data Science is most useful when it exists within the context of a business decision or goal. Our industry is maturing, and we need to show that our skills as Data Scientists can create high returns for what we invest into our teams. For us in Elkjøp, this means using Data Science to provide our end users with a personalised and seamless shopping experience, which in turn creates tangible business value.

In this talk I will discuss how we at Elkjøp are currently using Data Science to give our customers an improved shopping experience both in-store and online. Additionally we will also look at the issues that we face in achieving the goals we have set for ourselves, the lessons we’ve learnt, and our future goals for a more personalised customer experience.

Speaker(s):

Stephen Allwright

I'm a Data Scientist at Elkjøp Nordic with previous experience working as a Data Science Consultant for Sopra Steria. With a background in mathematics and a drive to help people, Data Science combines all of the aspects I enjoy about the business world. Originally for the UK, where I worked within the finance industry, I have been able to combine my analytical education and business experience to help create valuable Data Science solutions.

Type: Presentation, 45 min Language: En Tags: AI, ML, Deep learning Audience: Intermediate

Abstract:

By now, you should have heard of these buzzwords - AI, Machine Learning, and more recently, Deep Learning. But what exactly is Deep Learning, how it works, and more importantly, how do you actually get started with it?

In this session, Wei-Meng will explain Deep Learning so that it is easy to understand. You will learn what it means by back-propagation, gradient descent, loss functions, optimizers, and more. You will walk away from this session with a practical example on how to train a deep learning model to recognize objects. If you want to join in the AI bandwagon, this is a session not to miss!

Speaker(s):

Wei-Meng Lee

Wei-Meng Lee is a technologist and founder of Developer Learning Solutions (http://www.learn2develop.net), a technology company specializing in hands-on training on the latest Web and mobile technologies.

Wei-Meng speaks regularly at international conferences and has authored and co-authored numerous programming books.

Type: Short talk, 30 min Language: En Tags: AI, Cloud, Data Science, Legal Audience: Intermediate

Abstract:

In this talk, we will give an overview of and insight in some of the key legal aspects to consider when working with AI. How can you agree on contractual requirements for AI? Who's liable when AI goes wrong?

Speaker(s):

Kjetil Wick Sætre

Kjetil Wick Sætre is an associate in Advokatfirmaet Føyen Torkildsen AS. He works extensively with technology, media, IT contracts, and data privacy. Kjetil has previously worked at NRK (Norsk rikskringkasting) and the Norwegian Research Center for Computers and Law at the University of Oslo.

Type: presentation, 45 min Language: en Tags: ML Audience: Beginner

Abstract:

The advent of machine learning along with its integration with big data has enabled users to efficiently to develop solutions for innumerable use cases. A machine learning model consists of an algorithm which draws some meaningful correlation between the data without being tightly coupled to a specific set of rules. It's crucial to explain the subtle nuances of the network along with the use-case we are trying to solve. With the advent of technology, the quantity of data has increased which in turn has increased the need for resources to process the data while building a model. The main question, however, is to discuss the need to develop lightweight models keeping the performance of the system intact. To connect the dots, we will talk about the development of these applications specifically aimed to provide equally accurate results without using much of the resources. This is achieved by using image processing techniques along with optimizing the network architecture.

Speaker(s):

Akshay Bahadur

Akshay Bahadur's interest towards computer science sparked when he was working on a women's safety application aimed towards the women welfare in India and since then he has been incessantly working on improving my skills. He has made successful prototypes like autonomous car, alphabet recognition, cancer classification, gesture recognition using learning models. His ambition is to make valuable contribution towards ML community and leave a message of perseverance and tenacity. Currently, he is working as a software engineer at Symantec, India. He's is one out of 8 Google Developer Expert (Machine Learning) from India along with being one of 150 members worldwide for Intel Software Innovator program. His recent contribution on developing an Indian Sign Language Recognition (ISLAR) has been appreciated worldwide.

Type: short talk, 30 min Language: en Tags: Cloud Audience: Beginner

Abstract:

The cloud is a magic place. Your product teams create wonderful services; publish them for the world to see and then realize that this magic place has some very different rules.

This session will show a real-world story of how Vipps moved its traditional ops gradually to cloud-native in Azure. There will be some non-technical discussions about various Azure services.

This talk is for IT decision makers like architects, leaders but also agile coaches that can help the development teams to move to the cloud.

It is assumed that you understand the basic concept of the cloud, some technical understanding, and the wish of moving to Azure.

Speaker(s):

Sven Malvik

Sven is the leader of the platform team at Vipps. His job is to ensure that Vipps builds a solid, secure, and flexible foundation in Azure that the developers want to use. He has spoken at conferences like Microsoft Build, Javazone and various Meetup groups.

Type: short talk, 30 min Language: en Tags: AI, Data Science, Ethics Audience: Beginner

Abstract:

Over the years, businesses have come to realize that to have amazing growth and profitability using AI, it usually boils down to delivering great customer experiences. What if there was a way to enhancing the reach and scale of your human staff using AI such that you could augment, not automate? So that you could retain, not replace the expertise of your business users? My talk is about a unique slant of AI called human-centred AI, along with a playbook for architecting ML systems using microservices that has worked exceptionally well for some problems in retail.

Speaker(s):

Vivek Bharadwaj

I am a full-stack Data Scientist with over 12 years of experience in analytics and machine learning. Currently, I work for Australia's largest fashion e-commerce company called THE ICONIC and lead their marketing science function, where I have built machine learning models for churn, lifetime value and multi-channel attribution as well as mapped out customer journey events.

Type: presentation, 45 min Language: no Tags: Cloud, ML, Research Audience: Intermediate

Abstract:

I denne sesjonen skal vi snakke om dyp læring for segmentering av barnehjerter. Vi bruker state of the art nevrale nett for å segmentere hjerter med medfødt feil, hvor målet er å framstille hjertene i 3D for bedre operasjonsplanlegging. Vi skal gå igjennom arkitekturen vi bruker, teknologien bak, utfordringer og tips når man jobber med 3D bildedata.

Speaker(s):

Brede Bjørhovd

Brede is a senior data scientist at Sopra Steria, while there he has worked on mostly deep learning projects, ranging from automated design to customer segmentation. He has also worked in a computer vision start-up in Bergen.

Snorre Alm Harestad

Snorre Alm Harestad is an Oslo-based developer and data scientist with almost five years experience building business-critical, intelligent and cloud-based solutions for large Norwegian enterprises. He is currently working on an inter-disciplinary project together with clinicians attempting to automate medical image segmentation of organs for surgery planning and navigation. His role consists of developing architecture and infrastructure for training AI models utilising machine learning techniques such as neural networks, as well as the solution itself based on top of TensorFlow.

Type: short talk, 30 min Language: En Tags: AI, Data Science, ML, Research Audience: All

Abstract:

The language model BERT is a huge break-through in NLP, published in 2018 by Google, with both trained models and code available under an extremely unrestrictive license. The models even support Norwegian Bokmål and Nynorsk, as well as several other low-resource languages.

This opens up new and exciting possibilities for ordinary companies without the resources of Google and Facebook, both in terms of computing power and datasets. What are these possibilities?

Speaker(s):

Sigrid L. Bjørndal

Sigrid L. Bjørndal is an Oslo-based data scientist and developer, who recently graduated from NTNU with a master in Machine Learning. She wrote her master thesis on applying recent developments in Natural Language Processing, including BERT, to a practical application for a large Norwegian bank. She is currently working for Sopra Steria together with clinicians on an inter-disciplinary project, where she is using AI to automate medical image segmentation of organs, with the goal of improving complex surgery planning and navigation.

Type: workshop, 90 min Language: En Tags: AI, Ethics, Fairness in ML, Research Audience: Intermediate

Abstract:

During this workshop we'll teach you what you have to know to account for fairness when building machine learning pipelines. The first hour will set the theorethical background necessary for the second hands-on part. Audience: Basic ML knowledge is required. We assume you know how to work with data and train a simple ML model. Basic math undertanding of probability.

Speaker(s):

Marco Bertani-Økland

Mathematician and software engineer who cares about building a sustainable future with technology. Working on Responsible AI in both industry and academy.

Josephine Honoré

Josephine Honoré er M.Sc. i Software Development og jobber som kunnskapsingeniør i Computas. Hun har skrevet masteropgave omkring fair anbefalingssystemer og interesserer sig særligt for temaer inden for retfærdig, ansvarlig og forklarbar maskinlæring.

Type: Short talk, 30 min Language: En Tags: Data Science, ML, Open standards Audience: Intermediate

Abstract:

The use of Machine Learning in all application areas is on the rise. Once a good model is created, it needs to be serialized to be transmitted and deployed, i.e. positioned for producing predictions for new cases. This is often difficult because model building and deployment are typically done by different teams, using different programming environments and languages. In this talk we will explain open standards (PMML, PFA, ONNX) that have made model exchange and deployment easier and show how they are or can be used in some applications, including healthcare.

Speaker(s):

Svetlana Levitan

Svetlana is a Senior Developer Advocate at IBM. She works on PMML and ONNX, open standards for ML model deployment. Svetlana presents workshops, conference talks, meetups around the world.

Type: Short talk, 30 min Language: En Tags: AI, ML, Cloud Audience: Intermediate

Abstract:

This talk will be both introduction to Generative Adversarial Networks, and to Azure Machine Learning. I will use GAN as an example to show how convenient it is to perform computationally intensive neural network training on Azure Machine Learning, and discuss what advantages it gives to the Data Scientist.

Speaker(s):

Dmitry Soshnikov

Cloud Developer Advocate at Microsoft, Associate Professor at MIPT, HSE and MAI, Amateur Digital Artist, Father and Geek.

Type: Short talk, 30 min Language: En Tags: AI, ML Audience: Beginner

Abstract:

On-Device Machine Learning will explore ways to train and run a Deep Learning Model on your edge devices such as Smartphones, IoT Devices and devices without an OS like Microcontroller units (MCU). This presentation will explore next generation techniques to run a Machine Learning model that can be power efficient, respect Data privacy and security, and computationally efficient without losing any performance.

Speaker(s):

Kshitiz Rimal

Kshitiz Rimal is an AI Developer from Nepal. He is Google Developers Expert (GDE) on Machine Learning, Intel AI Student Ambassador and currently a co-founder and Head of Research at Artificial Intelligence for Development, a not-for-profit research organization in Nepal.
For the past 8 years he has been developing software and recently, for the past 3 years he is involved with Deep Learning. He is one of the founding members of the first community on Deep Learning established in Nepal. He has been developing projects around Deep Learning, delivering hands-on workshops on that particular technology, organizing meetups, presenting at international conferences and delivering AI training all around the world, which includes, USA, Singapore, China, Switzerland, Sweden and many others.
He is a 1st-runner up winner in a competition on Disaster relief and response, called "Call for Code 2018", for his project PD3R, which was on Structural Retrofitting using AI. He recently delivered a demo presentation and co-instructed a hands-on workshop at AI for Good Global Summit 2019, in Geneva, for his project called Cash Recognition for Visually Impaired, which is under the theme of AI for Accessibility. He is passionate about AI and working actively how it can be used for the good of mankind.

Type: Short talk, 30 min Language: En Tags: Cloud, Data Science Audience: Intermediate

Abstract:

Building analytics pipelines that can ingest data at a scale is not a simple task. However in this session I want to show you how you can build a serverless analytics pipeline using different serverless components and 0 code.

This pipeline is design to scale and to be highly available and will be hosted in the cloud. This is a very hands on session where we are going to use different services like: Kinesis Firehose, AWS Glue, AWS Athena and Quicksight.

Speaker(s):

Marcia Villalba

Marcia is a developer advocate for AWS and the host of FooBar a youtube channel (https://bit.ly/foobar-youtube) where she publishes content every week, related to serverless and the cloud.

Type: Short talk, 30 min Language: En Tags: AI, Ethics, ML Audience: Intermediate

Abstract:

Research have shown that emotions play an integral role in decision making, cognition, perception, learning and more. If we want our computers to be intelligent and be able to interact with us we need to ensure that they are able to recognize, understand and express emotions. This is the basic assumption of the field of Affective Computing. In this talk I will give an overview of Affective computing and how it can be applied in order to make our interaction with machines more suitable to us as humans.

First, I will give an introduction to the field starting with established findings from the field of psychology on how we best can measure emotions.

Then, I will describe how the field of Affective Computing has transformed from its origin in the 90’s until now when it is an established research field. I will highlight some of the technology enablers that has made Affective Computing a hot topic nowadays and give some examples of API and services that we as developers can use as of today.

In the second part of my talk, I will give some examples on application scenarios across various fields (retail, medical, education and social). After that I will be show casing what is in the front line now. I will conclude my presentation with some recommendations on how this affects us as developers going forward.

Speaker(s):

Håkan Silfvernagel

Håkan is working as Manager AI and Big Data at Miles AS.

He is active as Chairman of the Norwegian .NET User Group Oslo and as an Ambassador for Oslo.AI.

Håkan is also a Microsoft AI MVP.

Type: Short talk, 30 min Language: En Tags: ML Audience: Beginner

Abstract:

In order to start out with machine learning you typically would need to learn Python, Tensorflow, Jupyter Notebook etc. But what if you could run your machine learning straight in the browser. This can be done through Tensorflow.js. In this session you will get an introduction so that you can use it in your own projects.

This session will give you an introduction to what Machine learning is and what types of problem you can solve. TensorFlow as a library will be introduced and then TensorFlow.js will be presented with a focus on how you can use a machine learning model in your JavaScript application.

Next, we will build an image classification web app that uses a predefined TensorFlow model.

Finally, some examples on how TensorFlow.js is used in commercial applications will be given.

Speaker(s):

Håkan Silfvernagel

Håkan is working as Manager AI and Big Data at Miles AS.

He is active as Chairman of the Norwegian .NET User Group Oslo and as an Ambassador for Oslo.AI.

Håkan is also a Microsoft AI MVP.

Type: Short talk, 30 min Language: En Tags: AI, Data Science, ML Audience: Intermediate

Abstract:

What is deep learning? How does it work and where can it be used?

In this presentation we will talk about the problems related to deep learning and the improvements that has made it an interesting option for machine learning.

We will talk about convolutional neural networks and learn how they work.

Speaker(s):

Heli Helskyaho

Heli Helskyaho is the CEO for Miracle Finland Oy. Heli holds a Master’s degree (Computer Science) at the University of Helsinki and she is specialized on databases. At the moment she is working on her doctoral studies, researching and teaching at the University of Helsinki. Heli has been working on IT since 1990. Heli is an Oracle ACE Director, an Oracle Groundbreaker Ambassador, and a frequent speaker in many conferences. She is the author of Oracle SQL Developer Data Modeler for Database Design Mastery (Oracle Press 2015) and a co-author of Real World SQL and PL/SQL: Advice from the Experts (Oracle Press 2016).

Heli was listed as one of the TOP 100 influences on IT sector in Finland in 2015, in 2016, in 2017, in 2018, and again in 2019.

Type: Presentation, 45 min Language: En Tags: AI, ML Audience: Beginner

Abstract:

Machine Learning is Beautiful, especially in the JavaScript. Watch as we use JS to explore AI on the edge. That means plugins, mobile and even the browser! Let's explore it together!

Speaker(s):

Gant G Laborde

Gant Laborde is an owner of Infinite Red, mentor, adjunct professor, published author, and award-winning speaker. Follow Gant’s adventures at https://gantlaborde.com/.

Gant is a GDE in Web/ML, Cloudinary MDE, and Oracle Groundbreaker Ambassador.

Type: Presentation, 45 min Language: En Tags: Cloud, Data Science, ML Audience: Intermediate

Abstract:

One of the hottest topics in database land these days is BigQuery ML. A new way to use machine learning on top of tabular data straight on your tables without leaving the query editor.

With BigQuery ML, you can build machine learning models without leaving the database environment and training it on massive datasets.

In this demo session, we are going to demonstrate common marketing Machine Learning use cases how to build, train, eval and predict, your own scalable machine learning models using SQL language.

The audience will get first hand experience how to write CREATE MODEL sql syntax to build machine learning models such as:
- Multiclass logistic regression for classification
- K-means clustering
- Import TensorFlow models for prediction in BigQuery

Models are trained and accessed in BigQuery using SQL — a language data analysts know. This enables business decision making through predictive analytics across the organization without leaving the query editor

Speaker(s):

Marton Kodok

Márton is a Google Developer Expert(GDE) senior software architect at REEA.net. A romanian hero on StackOverflow with 172k reputation points. He led the implementation of complex and distributed systems serving millions of users for companies like FreeLogoServices, LogoMix, WaterSmart, Ausschreibungsdienste and many more.

Active contributor for open-source solutions like Beanstalkd console, and Riak admin interface. Expert in databases and systems like Google BigQuery, Elasticsearch, Redis.

Type: Short talk, 30 min Language: En Tags: AI, Data Science, ML Audience: Advanced

Abstract:

Three things are certain in life: death, taxes, and the fact that gradient boosting is awesome. XGBoost, LightGBM or CatBoost; there is a flavor of boosting for everyone, and they all get the job done whether you're competing on Kaggle or solving problems in your day job. 

At Kolonial.no - Norways largest online grocery player by name and tech/logistics company by trade - we use boosting models for forecasting and a couple of other areas, to make sure we keep delivering on our promise to create freedom and flow in our customers' daily lives. We have built a set of tools around common (and not so common!) machine learning pipeline functionality for tuning, training and making predictions with boosting models, so data scientists don't have to write boilerplate code and we can get up and running with new projects and pipelines in a few days instead of weeks.

Want to know why and how boosting will solve all your problems? Do you want to be that data scientist who gets things done by simply making great pipelines with just the right amount of feature engineering, .fit(...) and .predict(...) with the right algorithms and hyperparameters, and robust validation? This talk is for you!

Speaker(s):

Kjetil Åmdal-Sævik

Kjetil is Data Science Manager in Kolonial.no, which has been his dream job ever since he learned that ML is a thing and online groceries is a thing. He loves to backprop gradients and boost trees.

Type: Short talk, 30 min Language: En Tags: Data Science, ML, Research Audience: Advanced

Abstract:

Calculation of similarity between two entities is a key step in several data mining processes. While there are several common similarity measures for continuous data, there is little work for categorical data. Most approaches are purely data-driven and don’t consider the inherent dependencies of complex domains such as geological structures etc. We propose two new similarity measures that take into account semantic information to calculate the similarity between two categorical values. We apply our methods to a specific complex data mining task in the oil and gas industry: reservoir analogue identification.

Speaker(s):

Summaya Mumtaz

Summaya is a PhD research fellow at SIRIUS (Centre for Scalable Data Access for Oil and Gas), University of Oslo. Predictive analytics is the use of statistics, machine learning and modelling to analyze current and historical facts to make predictions about future events. However, standard machine learning techniques fail to produce quality predictions in complex domains. Currently, Summaya is working to add domain information into ML models for improved predictions.

Type: Short talk, 30 min Language: En Tags: AI, Cloud, Data Science, Ethics, ML Audience: Intermediate

Abstract:

We have heard about AI and its many applications but also it is importance to know and understand why we need multidisciplinary teams (diversity) to build AI knowledge and AI based solutions for the world, as well as understanding the importance of human-centered design for AI solutions.

This talk's aim is to share experience about AI diversity teams as well as good practices for designing.

Speaker(s):

Lesly Zerna

Gooogle Developer Expert in Machine Learning, co founder Mentor Her project to encourage girls to join tech careers. Mentor at Udacity's nanodegree of Business Analytics. International speaker. TEDx speaker 2018. Blogger at medium.com/@leslysandra about trips and tech. Instructor and professor at Catholic University in Bolivia. Ambassador and coordinator for City.AI in latino america. Currently, leading the innovation, research and dev department at the e-gov agency of Bolivia.

Type: Presentation, 45 min Language: En Tags: AI, Cloud, Ethics, ML, Privacy Audience: Beginner

Abstract:

Edge computing helps to break beyond the limitations imposed by, now, traditional cloud solutions. Some of the reasons might be privacy concerns, reducing the need for heavy processing resources, reducing the amount of data that is sent over the network – just to mention a few.

In this talk, we will introduce the concept and benefits of Edge Computing, how such devices can be built using affordable hardware and we will look at examples on how IoT Edge devices are in practice as well as comparing Edge Computing with other options.

As a live demo, we will be using a system built using Google Coral IoT Edge device. This is an example to process video streams on the Edge and designed to keep the privacy of the people intact; without leaking faces and identity of the people to a 3rd party. In addition to standard video processing, we will show advanced ML techniques and models that are processed on to the device to demonstrate the power and flexibility of the Edge devices nowadays.

Speaker(s):

Rustam Mehmandarov

Passionate computer scientist. Java Champion and Google Developers Expert for Cloud. Public speaker. Ex-leader of JavaZone and Norwegian JUG – javaBin.

Tannaz N. Roshandel

Tannaz works as a head engineer at the University of Oslo, where she is building an open source cloud service for the research and education sector in Norway. She has a background in robotics and is passionate about computer ethics.

Type: Short talk, 30 min Language: En Tags: Data Science, User research, UX, Business Audience: Intermediate

Abstract:

Data Science is most useful when it exists within the context of a business decision or goal. Our industry is maturing, and we need to show that our skills as Data Scientists can create high returns for what we invest into our teams. For us in Elkjøp, this means using Data Science to provide our end users with a personalised and seamless shopping experience, which in turn creates tangible business value.

In this talk I will discuss how we at Elkjøp are currently using Data Science to give our customers an improved shopping experience both in-store and online. Additionally we will also look at the issues that we face in achieving the goals we have set for ourselves, the lessons we’ve learnt, and our future goals for a more personalised customer experience.

Speaker(s):

Stephen Allwright

I'm a Data Scientist at Elkjøp Nordic with previous experience working as a Data Science Consultant for Sopra Steria. With a background in mathematics and a drive to help people, Data Science combines all of the aspects I enjoy about the business world. Originally for the UK, where I worked within the finance industry, I have been able to combine my analytical education and business experience to help create valuable Data Science solutions.

Type: Presentation, 45 min Language: En Tags: AI, ML, Deep learning Audience: Intermediate

Abstract:

By now, you should have heard of these buzzwords - AI, Machine Learning, and more recently, Deep Learning. But what exactly is Deep Learning, how it works, and more importantly, how do you actually get started with it?

In this session, Wei-Meng will explain Deep Learning so that it is easy to understand. You will learn what it means by back-propagation, gradient descent, loss functions, optimizers, and more. You will walk away from this session with a practical example on how to train a deep learning model to recognize objects. If you want to join in the AI bandwagon, this is a session not to miss!

Speaker(s):

Wei-Meng Lee

Wei-Meng Lee is a technologist and founder of Developer Learning Solutions (http://www.learn2develop.net), a technology company specializing in hands-on training on the latest Web and mobile technologies.

Wei-Meng speaks regularly at international conferences and has authored and co-authored numerous programming books.

Type: Short talk, 30 min Language: En Tags: AI, Cloud, Data Science, Legal Audience: Intermediate

Abstract:

In this talk, we will give an overview of and insight in some of the key legal aspects to consider when working with AI. How can you agree on contractual requirements for AI? Who's liable when AI goes wrong?

Speaker(s):

Kjetil Wick Sætre

Kjetil Wick Sætre is an associate in Advokatfirmaet Føyen Torkildsen AS. He works extensively with technology, media, IT contracts, and data privacy. Kjetil has previously worked at NRK (Norsk rikskringkasting) and the Norwegian Research Center for Computers and Law at the University of Oslo.

Type: presentation, 45 min Language: en Tags: ML Audience: Beginner

Abstract:

The advent of machine learning along with its integration with big data has enabled users to efficiently to develop solutions for innumerable use cases. A machine learning model consists of an algorithm which draws some meaningful correlation between the data without being tightly coupled to a specific set of rules. It's crucial to explain the subtle nuances of the network along with the use-case we are trying to solve. With the advent of technology, the quantity of data has increased which in turn has increased the need for resources to process the data while building a model. The main question, however, is to discuss the need to develop lightweight models keeping the performance of the system intact. To connect the dots, we will talk about the development of these applications specifically aimed to provide equally accurate results without using much of the resources. This is achieved by using image processing techniques along with optimizing the network architecture.

Speaker(s):

Akshay Bahadur

Akshay Bahadur's interest towards computer science sparked when he was working on a women's safety application aimed towards the women welfare in India and since then he has been incessantly working on improving my skills. He has made successful prototypes like autonomous car, alphabet recognition, cancer classification, gesture recognition using learning models. His ambition is to make valuable contribution towards ML community and leave a message of perseverance and tenacity. Currently, he is working as a software engineer at Symantec, India. He's is one out of 8 Google Developer Expert (Machine Learning) from India along with being one of 150 members worldwide for Intel Software Innovator program. His recent contribution on developing an Indian Sign Language Recognition (ISLAR) has been appreciated worldwide.

Type: Short talk, 30 min Language: En Tags: Data Science, ML, Open standards Audience: Intermediate

Abstract:

The use of Machine Learning in all application areas is on the rise. Once a good model is created, it needs to be serialized to be transmitted and deployed, i.e. positioned for producing predictions for new cases. This is often difficult because model building and deployment are typically done by different teams, using different programming environments and languages. In this talk we will explain open standards (PMML, PFA, ONNX) that have made model exchange and deployment easier and show how they are or can be used in some applications, including healthcare.

Speaker(s):

Svetlana Levitan

Svetlana is a Senior Developer Advocate at IBM. She works on PMML and ONNX, open standards for ML model deployment. Svetlana presents workshops, conference talks, meetups around the world.

Type: Short talk, 30 min Language: En Tags: AI, Cloud, Data Science, Ethics, ML Audience: Intermediate

Abstract:

We have heard about AI and its many applications but also it is importance to know and understand why we need multidisciplinary teams (diversity) to build AI knowledge and AI based solutions for the world, as well as understanding the importance of human-centered design for AI solutions.

This talk's aim is to share experience about AI diversity teams as well as good practices for designing.

Speaker(s):

Lesly Zerna

Gooogle Developer Expert in Machine Learning, co founder Mentor Her project to encourage girls to join tech careers. Mentor at Udacity's nanodegree of Business Analytics. International speaker. TEDx speaker 2018. Blogger at medium.com/@leslysandra about trips and tech. Instructor and professor at Catholic University in Bolivia. Ambassador and coordinator for City.AI in latino america. Currently, leading the innovation, research and dev department at the e-gov agency of Bolivia.

Type: short talk, 30 min Language: en Tags: AI, Data Science, Ethics Audience: Beginner

Abstract:

Over the years, businesses have come to realize that to have amazing growth and profitability using AI, it usually boils down to delivering great customer experiences. What if there was a way to enhancing the reach and scale of your human staff using AI such that you could augment, not automate? So that you could retain, not replace the expertise of your business users? My talk is about a unique slant of AI called human-centred AI, along with a playbook for architecting ML systems using microservices that has worked exceptionally well for some problems in retail.

Speaker(s):

Vivek Bharadwaj

I am a full-stack Data Scientist with over 12 years of experience in analytics and machine learning. Currently, I work for Australia's largest fashion e-commerce company called THE ICONIC and lead their marketing science function, where I have built machine learning models for churn, lifetime value and multi-channel attribution as well as mapped out customer journey events.

Type: Short talk, 30 min Language: En Tags: ML Audience: Beginner

Abstract:

In order to start out with machine learning you typically would need to learn Python, Tensorflow, Jupyter Notebook etc. But what if you could run your machine learning straight in the browser. This can be done through Tensorflow.js. In this session you will get an introduction so that you can use it in your own projects.

This session will give you an introduction to what Machine learning is and what types of problem you can solve. TensorFlow as a library will be introduced and then TensorFlow.js will be presented with a focus on how you can use a machine learning model in your JavaScript application.

Next, we will build an image classification web app that uses a predefined TensorFlow model.

Finally, some examples on how TensorFlow.js is used in commercial applications will be given.

Speaker(s):

Håkan Silfvernagel

Håkan is working as Manager AI and Big Data at Miles AS.

He is active as Chairman of the Norwegian .NET User Group Oslo and as an Ambassador for Oslo.AI.

Håkan is also a Microsoft AI MVP.

Type: workshop, 90 min Language: En Tags: AI, Ethics, Fairness in ML, Research Audience: Intermediate

Abstract:

During this workshop we'll teach you what you have to know to account for fairness when building machine learning pipelines. The first hour will set the theorethical background necessary for the second hands-on part. Audience: Basic ML knowledge is required. We assume you know how to work with data and train a simple ML model. Basic math undertanding of probability.

Speaker(s):

Marco Bertani-Økland

Mathematician and software engineer who cares about building a sustainable future with technology. Working on Responsible AI in both industry and academy.

Josephine Honoré

Josephine Honoré er M.Sc. i Software Development og jobber som kunnskapsingeniør i Computas. Hun har skrevet masteropgave omkring fair anbefalingssystemer og interesserer sig særligt for temaer inden for retfærdig, ansvarlig og forklarbar maskinlæring.

Type: Short talk, 30 min Language: En Tags: AI, ML Audience: Beginner

Abstract:

On-Device Machine Learning will explore ways to train and run a Deep Learning Model on your edge devices such as Smartphones, IoT Devices and devices without an OS like Microcontroller units (MCU). This presentation will explore next generation techniques to run a Machine Learning model that can be power efficient, respect Data privacy and security, and computationally efficient without losing any performance.

Speaker(s):

Kshitiz Rimal

Kshitiz Rimal is an AI Developer from Nepal. He is Google Developers Expert (GDE) on Machine Learning, Intel AI Student Ambassador and currently a co-founder and Head of Research at Artificial Intelligence for Development, a not-for-profit research organization in Nepal.
For the past 8 years he has been developing software and recently, for the past 3 years he is involved with Deep Learning. He is one of the founding members of the first community on Deep Learning established in Nepal. He has been developing projects around Deep Learning, delivering hands-on workshops on that particular technology, organizing meetups, presenting at international conferences and delivering AI training all around the world, which includes, USA, Singapore, China, Switzerland, Sweden and many others.
He is a 1st-runner up winner in a competition on Disaster relief and response, called "Call for Code 2018", for his project PD3R, which was on Structural Retrofitting using AI. He recently delivered a demo presentation and co-instructed a hands-on workshop at AI for Good Global Summit 2019, in Geneva, for his project called Cash Recognition for Visually Impaired, which is under the theme of AI for Accessibility. He is passionate about AI and working actively how it can be used for the good of mankind.

Type: Presentation, 45 min Language: En Tags: AI, Cloud, Ethics, ML, Privacy Audience: Beginner

Abstract:

Edge computing helps to break beyond the limitations imposed by, now, traditional cloud solutions. Some of the reasons might be privacy concerns, reducing the need for heavy processing resources, reducing the amount of data that is sent over the network – just to mention a few.

In this talk, we will introduce the concept and benefits of Edge Computing, how such devices can be built using affordable hardware and we will look at examples on how IoT Edge devices are in practice as well as comparing Edge Computing with other options.

As a live demo, we will be using a system built using Google Coral IoT Edge device. This is an example to process video streams on the Edge and designed to keep the privacy of the people intact; without leaking faces and identity of the people to a 3rd party. In addition to standard video processing, we will show advanced ML techniques and models that are processed on to the device to demonstrate the power and flexibility of the Edge devices nowadays.

Speaker(s):

Rustam Mehmandarov

Passionate computer scientist. Java Champion and Google Developers Expert for Cloud. Public speaker. Ex-leader of JavaZone and Norwegian JUG – javaBin.

Tannaz N. Roshandel

Tannaz works as a head engineer at the University of Oslo, where she is building an open source cloud service for the research and education sector in Norway. She has a background in robotics and is passionate about computer ethics.

Type: Short talk, 30 min Language: En Tags: Cloud, Data Science Audience: Intermediate

Abstract:

Building analytics pipelines that can ingest data at a scale is not a simple task. However in this session I want to show you how you can build a serverless analytics pipeline using different serverless components and 0 code.

This pipeline is design to scale and to be highly available and will be hosted in the cloud. This is a very hands on session where we are going to use different services like: Kinesis Firehose, AWS Glue, AWS Athena and Quicksight.

Speaker(s):

Marcia Villalba

Marcia is a developer advocate for AWS and the host of FooBar a youtube channel (https://bit.ly/foobar-youtube) where she publishes content every week, related to serverless and the cloud.

Type: Short talk, 30 min Language: En Tags: AI, Ethics, ML Audience: Intermediate

Abstract:

Research have shown that emotions play an integral role in decision making, cognition, perception, learning and more. If we want our computers to be intelligent and be able to interact with us we need to ensure that they are able to recognize, understand and express emotions. This is the basic assumption of the field of Affective Computing. In this talk I will give an overview of Affective computing and how it can be applied in order to make our interaction with machines more suitable to us as humans.

First, I will give an introduction to the field starting with established findings from the field of psychology on how we best can measure emotions.

Then, I will describe how the field of Affective Computing has transformed from its origin in the 90’s until now when it is an established research field. I will highlight some of the technology enablers that has made Affective Computing a hot topic nowadays and give some examples of API and services that we as developers can use as of today.

In the second part of my talk, I will give some examples on application scenarios across various fields (retail, medical, education and social). After that I will be show casing what is in the front line now. I will conclude my presentation with some recommendations on how this affects us as developers going forward.

Speaker(s):

Håkan Silfvernagel

Håkan is working as Manager AI and Big Data at Miles AS.

He is active as Chairman of the Norwegian .NET User Group Oslo and as an Ambassador for Oslo.AI.

Håkan is also a Microsoft AI MVP.

Type: Presentation, 45 min Language: En Tags: AI, ML, Deep learning Audience: Intermediate

Abstract:

By now, you should have heard of these buzzwords - AI, Machine Learning, and more recently, Deep Learning. But what exactly is Deep Learning, how it works, and more importantly, how do you actually get started with it?

In this session, Wei-Meng will explain Deep Learning so that it is easy to understand. You will learn what it means by back-propagation, gradient descent, loss functions, optimizers, and more. You will walk away from this session with a practical example on how to train a deep learning model to recognize objects. If you want to join in the AI bandwagon, this is a session not to miss!

Speaker(s):

Wei-Meng Lee

Wei-Meng Lee is a technologist and founder of Developer Learning Solutions (http://www.learn2develop.net), a technology company specializing in hands-on training on the latest Web and mobile technologies.

Wei-Meng speaks regularly at international conferences and has authored and co-authored numerous programming books.

Type: Short talk, 30 min Language: En Tags: AI, Cloud, Data Science, Legal Audience: Intermediate

Abstract:

In this talk, we will give an overview of and insight in some of the key legal aspects to consider when working with AI. How can you agree on contractual requirements for AI? Who's liable when AI goes wrong?

Speaker(s):

Kjetil Wick Sætre

Kjetil Wick Sætre is an associate in Advokatfirmaet Føyen Torkildsen AS. He works extensively with technology, media, IT contracts, and data privacy. Kjetil has previously worked at NRK (Norsk rikskringkasting) and the Norwegian Research Center for Computers and Law at the University of Oslo.

Type: Presentation, 45 min Language: En Tags: Cloud, Data Science, ML Audience: Intermediate

Abstract:

One of the hottest topics in database land these days is BigQuery ML. A new way to use machine learning on top of tabular data straight on your tables without leaving the query editor.

With BigQuery ML, you can build machine learning models without leaving the database environment and training it on massive datasets.

In this demo session, we are going to demonstrate common marketing Machine Learning use cases how to build, train, eval and predict, your own scalable machine learning models using SQL language.

The audience will get first hand experience how to write CREATE MODEL sql syntax to build machine learning models such as:
- Multiclass logistic regression for classification
- K-means clustering
- Import TensorFlow models for prediction in BigQuery

Models are trained and accessed in BigQuery using SQL — a language data analysts know. This enables business decision making through predictive analytics across the organization without leaving the query editor

Speaker(s):

Marton Kodok

Márton is a Google Developer Expert(GDE) senior software architect at REEA.net. A romanian hero on StackOverflow with 172k reputation points. He led the implementation of complex and distributed systems serving millions of users for companies like FreeLogoServices, LogoMix, WaterSmart, Ausschreibungsdienste and many more.

Active contributor for open-source solutions like Beanstalkd console, and Riak admin interface. Expert in databases and systems like Google BigQuery, Elasticsearch, Redis.

Type: presentation, 45 min Language: no Tags: Cloud, ML, Research Audience: Intermediate

Abstract:

I denne sesjonen skal vi snakke om dyp læring for segmentering av barnehjerter. Vi bruker state of the art nevrale nett for å segmentere hjerter med medfødt feil, hvor målet er å framstille hjertene i 3D for bedre operasjonsplanlegging. Vi skal gå igjennom arkitekturen vi bruker, teknologien bak, utfordringer og tips når man jobber med 3D bildedata.

Speaker(s):

Brede Bjørhovd

Brede is a senior data scientist at Sopra Steria, while there he has worked on mostly deep learning projects, ranging from automated design to customer segmentation. He has also worked in a computer vision start-up in Bergen.

Snorre Alm Harestad

Snorre Alm Harestad is an Oslo-based developer and data scientist with almost five years experience building business-critical, intelligent and cloud-based solutions for large Norwegian enterprises. He is currently working on an inter-disciplinary project together with clinicians attempting to automate medical image segmentation of organs for surgery planning and navigation. His role consists of developing architecture and infrastructure for training AI models utilising machine learning techniques such as neural networks, as well as the solution itself based on top of TensorFlow.

Type: Short talk, 30 min Language: En Tags: Data Science, User research, UX, Business Audience: Intermediate

Abstract:

Data Science is most useful when it exists within the context of a business decision or goal. Our industry is maturing, and we need to show that our skills as Data Scientists can create high returns for what we invest into our teams. For us in Elkjøp, this means using Data Science to provide our end users with a personalised and seamless shopping experience, which in turn creates tangible business value.

In this talk I will discuss how we at Elkjøp are currently using Data Science to give our customers an improved shopping experience both in-store and online. Additionally we will also look at the issues that we face in achieving the goals we have set for ourselves, the lessons we’ve learnt, and our future goals for a more personalised customer experience.

Speaker(s):

Stephen Allwright

I'm a Data Scientist at Elkjøp Nordic with previous experience working as a Data Science Consultant for Sopra Steria. With a background in mathematics and a drive to help people, Data Science combines all of the aspects I enjoy about the business world. Originally for the UK, where I worked within the finance industry, I have been able to combine my analytical education and business experience to help create valuable Data Science solutions.

Type: Short talk, 30 min Language: En Tags: AI, Data Science, ML Audience: Intermediate

Abstract:

What is deep learning? How does it work and where can it be used?

In this presentation we will talk about the problems related to deep learning and the improvements that has made it an interesting option for machine learning.

We will talk about convolutional neural networks and learn how they work.

Speaker(s):

Heli Helskyaho

Heli Helskyaho is the CEO for Miracle Finland Oy. Heli holds a Master’s degree (Computer Science) at the University of Helsinki and she is specialized on databases. At the moment she is working on her doctoral studies, researching and teaching at the University of Helsinki. Heli has been working on IT since 1990. Heli is an Oracle ACE Director, an Oracle Groundbreaker Ambassador, and a frequent speaker in many conferences. She is the author of Oracle SQL Developer Data Modeler for Database Design Mastery (Oracle Press 2015) and a co-author of Real World SQL and PL/SQL: Advice from the Experts (Oracle Press 2016).

Heli was listed as one of the TOP 100 influences on IT sector in Finland in 2015, in 2016, in 2017, in 2018, and again in 2019.

Type: Short talk, 30 min Language: En Tags: AI, ML, Cloud Audience: Intermediate

Abstract:

This talk will be both introduction to Generative Adversarial Networks, and to Azure Machine Learning. I will use GAN as an example to show how convenient it is to perform computationally intensive neural network training on Azure Machine Learning, and discuss what advantages it gives to the Data Scientist.

Speaker(s):

Dmitry Soshnikov

Cloud Developer Advocate at Microsoft, Associate Professor at MIPT, HSE and MAI, Amateur Digital Artist, Father and Geek.

Type: Presentation, 45 min Language: En Tags: AI, ML Audience: Beginner

Abstract:

Machine Learning is Beautiful, especially in the JavaScript. Watch as we use JS to explore AI on the edge. That means plugins, mobile and even the browser! Let's explore it together!

Speaker(s):

Gant G Laborde

Gant Laborde is an owner of Infinite Red, mentor, adjunct professor, published author, and award-winning speaker. Follow Gant’s adventures at https://gantlaborde.com/.

Gant is a GDE in Web/ML, Cloudinary MDE, and Oracle Groundbreaker Ambassador.

Type: Short talk, 30 min Language: En Tags: AI, Data Science, ML Audience: Advanced

Abstract:

Three things are certain in life: death, taxes, and the fact that gradient boosting is awesome. XGBoost, LightGBM or CatBoost; there is a flavor of boosting for everyone, and they all get the job done whether you're competing on Kaggle or solving problems in your day job. 

At Kolonial.no - Norways largest online grocery player by name and tech/logistics company by trade - we use boosting models for forecasting and a couple of other areas, to make sure we keep delivering on our promise to create freedom and flow in our customers' daily lives. We have built a set of tools around common (and not so common!) machine learning pipeline functionality for tuning, training and making predictions with boosting models, so data scientists don't have to write boilerplate code and we can get up and running with new projects and pipelines in a few days instead of weeks.

Want to know why and how boosting will solve all your problems? Do you want to be that data scientist who gets things done by simply making great pipelines with just the right amount of feature engineering, .fit(...) and .predict(...) with the right algorithms and hyperparameters, and robust validation? This talk is for you!

Speaker(s):

Kjetil Åmdal-Sævik

Kjetil is Data Science Manager in Kolonial.no, which has been his dream job ever since he learned that ML is a thing and online groceries is a thing. He loves to backprop gradients and boost trees.

Type: short talk, 30 min Language: En Tags: AI, Data Science, ML, Research Audience: All

Abstract:

The language model BERT is a huge break-through in NLP, published in 2018 by Google, with both trained models and code available under an extremely unrestrictive license. The models even support Norwegian Bokmål and Nynorsk, as well as several other low-resource languages.

This opens up new and exciting possibilities for ordinary companies without the resources of Google and Facebook, both in terms of computing power and datasets. What are these possibilities?

Speaker(s):

Sigrid L. Bjørndal

Sigrid L. Bjørndal is an Oslo-based data scientist and developer, who recently graduated from NTNU with a master in Machine Learning. She wrote her master thesis on applying recent developments in Natural Language Processing, including BERT, to a practical application for a large Norwegian bank. She is currently working for Sopra Steria together with clinicians on an inter-disciplinary project, where she is using AI to automate medical image segmentation of organs, with the goal of improving complex surgery planning and navigation.

Type: short talk, 30 min Language: en Tags: Cloud Audience: Beginner

Abstract:

The cloud is a magic place. Your product teams create wonderful services; publish them for the world to see and then realize that this magic place has some very different rules.

This session will show a real-world story of how Vipps moved its traditional ops gradually to cloud-native in Azure. There will be some non-technical discussions about various Azure services.

This talk is for IT decision makers like architects, leaders but also agile coaches that can help the development teams to move to the cloud.

It is assumed that you understand the basic concept of the cloud, some technical understanding, and the wish of moving to Azure.

Speaker(s):

Sven Malvik

Sven is the leader of the platform team at Vipps. His job is to ensure that Vipps builds a solid, secure, and flexible foundation in Azure that the developers want to use. He has spoken at conferences like Microsoft Build, Javazone and various Meetup groups.

Type: Short talk, 30 min Language: En Tags: Data Science, ML, Research Audience: Advanced

Abstract:

Calculation of similarity between two entities is a key step in several data mining processes. While there are several common similarity measures for continuous data, there is little work for categorical data. Most approaches are purely data-driven and don’t consider the inherent dependencies of complex domains such as geological structures etc. We propose two new similarity measures that take into account semantic information to calculate the similarity between two categorical values. We apply our methods to a specific complex data mining task in the oil and gas industry: reservoir analogue identification.

Speaker(s):

Summaya Mumtaz

Summaya is a PhD research fellow at SIRIUS (Centre for Scalable Data Access for Oil and Gas), University of Oslo. Predictive analytics is the use of statistics, machine learning and modelling to analyze current and historical facts to make predictions about future events. However, standard machine learning techniques fail to produce quality predictions in complex domains. Currently, Summaya is working to add domain information into ML models for improved predictions.