Wat we doen
Our very first Rotterdam Meetup is coming up! KPN ICT Consulting is hosting the 9th edition of the Machine Learning NL Meetup in their iconic KPN Tower along the river Maas. We have 3 in-depth talks about Applied Machine Learning from corporates and scale-ups. They will share real life applications based on real business cases. Free entrance and catering!
Never visited one of our meetups before? Here is an after movie of our latest event: https://youtu.be/cexA8Ht8xNI
> Open for all our members, including our Amsterdam crowd of course ;)
> All attendants need to register individually (no guest allowed)
5:30 PM Walk-in with sandwiches & drinks
6:30 PM Intro by Lars Crama - Strategy & Innovation Advisor. Tonight's moderator and inspirator. (https://www.linkedin.com/in/larscrama/)
6:35 PM Intro by Maarten Emons - Lead Consultant at KPN Consulting
6:40 PM Talk 1: Casper Lubbers - Consultant & Data Hacker at KPN Consulting - 'Advanced parallelism for analytics in Python'.
7:20 PM Talk 2: Samuel Blake - Senior Data Scientist at HAL24K – ‘The Future of Traffic Management’.
7:55 PM Talk 3: Stephen Galsworthy - Head of Data Science at Quby - we create Toon - 'AI and Machine Learning for the connected home - experiences from Toon.
8:30 PM Drinks!
9:30 PM End!
Visit https://aigents.co to discover more events and career opportunities for AI & Machine Learning Engineers.
Many thanks to the KPN team for hosting this meetup: Sjoerd Pilon, Marissa Helmich and Thijs Franssen.
At KPN ICT Consulting we're often faced with the challenge to scale the deployments of analytics Python code.
Dask provides a solution for this problem by leveraging the existing python ecosystem and scaling it, across the cores on your laptop – or by running within your existing Hadoop infrastructure with YARN as scheduler.
Often used tools such as Pandas, Numpy and Scikit-Learn are easily parallelised and scaled across multiple cores and even multiple computing nodes.
In this talk I will explain what Dask is, how we use it and, more importantly, how you can use it to scale your existing analytics Python code.
Quby is the creator and provider of Toon, a leading European smart home platform. We enable Toon users to control and monitor their homes using both an in-home display and app. As a data driven company, we use AI and machine learning to generate actionable insights for our end users. Using the data we collect via our IoT devices we have introduced multiple data driven services, including an energy waste checker and a boiler monitoring service.
In this talk, Stephen will describe how AI and machine learning is implemented on the Toon platform, and will show multiple use cases relating to the connected home. We’ll take a look at how Deep Learning algorithms are used to detect inefficient appliances from electricity meter data and how streaming algorithms allow users to be alerted to anomalies with their heating systems in near real-time. Stephen will share the experiences from the Data Science and Engineering teams at Quby with bringing data science algorithms from R&D to production and the lessons learned in offering multiple data driven services to hundreds of thousands of users on a daily basis.
Stephen Galsworthy is the Head of Data Science at Quby, the creator and provider of Toon, a leading European smart home platform. In this role, he is responsible for the development of data driven services for residential customers and partners such as utilities and insurance providers. Stephen holds both a Master’s degree and Ph.D. in Mathematics from Oxford University and has been leading Data Science teams since 2011.