WeAreDevelopers Live – Machine Learning Day
Exploring the depth and breadth of Machine Learning!
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Together with BOSCH we invite you to a full day of learning more about the intersection of mobility and code. Get to know more about how modern mobility is defined by an intricate interplay of hardware and software and how cars are not only connected to the road, but also to the cloud.
Coding the Future of Mobility features a variety of talks and a workshop, that give you valuable insights into the world of mobility - wether you join in-person or online.
Together with Bosch we invite you to a full day of learning more about the intersection of mobility and code. Get to know more about how modern mobility is defined by an intricate interplay of hardware and software and how cars are not only connected to the road, but also to the cloud.
Coding the Future of Mobility features a variety of talks and a workshop, that give you valuable insights into the world of mobility - wether you join in-person or online.
In this session Machine Learning Consultants Radu Pruna and Andras Palfi will showcase how the UiPath Platform can help you operationalize machine learning models and use them to construct end-to-end intelligent automation solutions. The session will start with a short introduction into Machine Learning after which VP of Automation Innovation Boris Krumrey will talk about how UiPath leverages Machine Learning to deliver value to its customers. The session will also include live demonstration of showcases in which machine learning models were used to solve specific business problems like improving the cash collection process.
Boris Krumrey is the Global VP Automation Innovations at UiPath is responsible to drive the UiPath Automation Innovation agenda to reboot work with customers and partners showing the art of the possible of Cognitive Automation at Scale. Boris invented and runs the UiPath Immersion Lab - a tailor-made, one or two-day session with UiPath Automation Innovation experts, and product management teams. It’s the environment where you’ll experience the latest advances in RPA, AI and Hyperautomation.
For years, companies built large Data lakes to make data available for analytical workloads and Big Data applications. The goal was to remove data silos and harmonize all data assets a company has to offer. However, most companies failed in this and the data lake became quite frustrating for people working with and using it. Now, a new promise emerges from the enterprise architecture: the data mesh. The data mesh aims at simplification, accepting the distributed nature of data. And – it seems that architects have learned from the past errors and with this approach. In this talk, we will look at what it is and how it is going to solve existing issues
Mario Meir-Huber is the Head of Data of Uniqa Insurance Group. In his role, Mario leads the groupstrategy on data together with a team of senior experts in this field. Next to his professional career, Mario is a frequent international speaker, writes articles about the topic and published several books and e-books on that. You can view his blog on: www.cloudvane.net
Advances in AI/ML tooling make it possible for anyone - not just data scientists - to create models that identify business risks, carry on conversations, drive cars, optimise vaccines, and even create art. This session will give an overview of AWS's AI/ML stack and then dive into a demo application: an attempt to teach a computer to reverse engineer knitting patterns, as part of Kris's evolving quest to build the world's first knitting replicator. (Yes, really.)
For the last twenty years Kris has been helping companies build amazing things online, first in Australia and now in Europe as part of the AWS Developer Relations team.
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.
Håkan holds a Master of Science degree in Electrical Engineering and in addition, he holds a Master’s degree in Leadership and Organizational behavior. He has 20 years’ experience of software development in various positions such as developer, tester, architect, project manager, scrum master, practice manager and team lead.
Håkan is Chairman of the local chapter of the Norwegian .NET User Group Oslo (NNUG) and is active as an Ambassador for Oslo.AI the local chapter for the global City.AI community. In addition, he is the co-founder of AI42, an online school for learning about AI and Data Science.
Håkan is a Microsoft Most Valuable Professional (MVP) in AI.
Currently Håkan is working as Manager AI and Big Data at Miles AS, a Norwegian consultancy company.
Although the serverless environment has been gaining popularity over
the past few years, its use for deployment of ML models has been
largely unexplored. In this talk I'll try to change that and discuss
our journey of using serverless (specifically AWS Lambda) to power
Slido's NLP-enabled features by going through it all: the good, the
bad and the ugly. Despite its limits, I'll try to show a couple
examples where it enabled projects that would not make it to
production otherwise.
Marek stumbled upon AI as a teenager when building soccer-playing
robots and quickly realized he is not smart enough to do all the
programming by himself. Since then, he's been trying to make machines
learn by themselves, particularly from text and images. He currently
leads the Data team at Slido, improving the way meetings are run
around the world. Previously, he was at DuckDuckGo, building a private
search engine.
Staying true to his roots, he tries to provide others with a chance to
have a similar experience by organizing the RoboCupJunior competition
and teaching aspiring Data Scientists about things they may not learn
otherwise: from cutting edge NLP methods to the strange world of UNIX
shells.
In this session Machine Learning Consultants Radu Pruna and Andras Palfi will showcase how the UiPath Platform can help you operationalize machine learning models and use them to construct end-to-end intelligent automation solutions. The session will start with a short introduction into Machine Learning after which VP of Automation Innovation Boris Krumrey will talk about how UiPath leverages Machine Learning to deliver value to its customers. The session will also include live demonstration of showcases in which machine learning models were used to solve specific business problems like improving the cash collection process.
Boris Krumrey is the Global VP Automation Innovations at UiPath is responsible to drive the UiPath Automation Innovation agenda to reboot work with customers and partners showing the art of the possible of Cognitive Automation at Scale. Boris invented and runs the UiPath Immersion Lab - a tailor-made, one or two-day session with UiPath Automation Innovation experts, and product management teams. It’s the environment where you’ll experience the latest advances in RPA, AI and Hyperautomation.
For years, companies built large Data lakes to make data available for analytical workloads and Big Data applications. The goal was to remove data silos and harmonize all data assets a company has to offer. However, most companies failed in this and the data lake became quite frustrating for people working with and using it. Now, a new promise emerges from the enterprise architecture: the data mesh. The data mesh aims at simplification, accepting the distributed nature of data. And – it seems that architects have learned from the past errors and with this approach. In this talk, we will look at what it is and how it is going to solve existing issues
Mario Meir-Huber is the Head of Data of Uniqa Insurance Group. In his role, Mario leads the groupstrategy on data together with a team of senior experts in this field. Next to his professional career, Mario is a frequent international speaker, writes articles about the topic and published several books and e-books on that. You can view his blog on: www.cloudvane.net
Advances in AI/ML tooling make it possible for anyone - not just data scientists - to create models that identify business risks, carry on conversations, drive cars, optimise vaccines, and even create art. This session will give an overview of AWS's AI/ML stack and then dive into a demo application: an attempt to teach a computer to reverse engineer knitting patterns, as part of Kris's evolving quest to build the world's first knitting replicator. (Yes, really.)
For the last twenty years Kris has been helping companies build amazing things online, first in Australia and now in Europe as part of the AWS Developer Relations team.
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.
Håkan holds a Master of Science degree in Electrical Engineering and in addition, he holds a Master’s degree in Leadership and Organizational behavior. He has 20 years’ experience of software development in various positions such as developer, tester, architect, project manager, scrum master, practice manager and team lead.
Håkan is Chairman of the local chapter of the Norwegian .NET User Group Oslo (NNUG) and is active as an Ambassador for Oslo.AI the local chapter for the global City.AI community. In addition, he is the co-founder of AI42, an online school for learning about AI and Data Science.
Håkan is a Microsoft Most Valuable Professional (MVP) in AI.
Currently Håkan is working as Manager AI and Big Data at Miles AS, a Norwegian consultancy company.
Although the serverless environment has been gaining popularity over
the past few years, its use for deployment of ML models has been
largely unexplored. In this talk I'll try to change that and discuss
our journey of using serverless (specifically AWS Lambda) to power
Slido's NLP-enabled features by going through it all: the good, the
bad and the ugly. Despite its limits, I'll try to show a couple
examples where it enabled projects that would not make it to
production otherwise.
Marek stumbled upon AI as a teenager when building soccer-playing
robots and quickly realized he is not smart enough to do all the
programming by himself. Since then, he's been trying to make machines
learn by themselves, particularly from text and images. He currently
leads the Data team at Slido, improving the way meetings are run
around the world. Previously, he was at DuckDuckGo, building a private
search engine.
Staying true to his roots, he tries to provide others with a chance to
have a similar experience by organizing the RoboCupJunior competition
and teaching aspiring Data Scientists about things they may not learn
otherwise: from cutting edge NLP methods to the strange world of UNIX
shells.
