Practical Machine Learning with H2O and StackNet
Details
[7 Sep Update]:
Please show your Eventbrite ticket when you sign in. Shop Direct office is next to the Grosvenor Hotel.
RSVP (Yes) will NOT guarantee you a seat.
If, unfortunately, you don't have a ticket, please wait until 6:30pm and see if there are empty seats. I am sorry for the inconvenience caused.
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[5 Sep Update]:
All Eventbrite tickets are gone. Thank you for the overwhelming response!!
Please ignore the RSVPs and waitlist - we found that the RSVP system is not suitable for the event as we need real names for security reason (for example, I cannot see the name of your +1). We have limited spaces (175) and we cannot offer any more tickets. I am sorry that we are unable to accommodate everyone. I will try to record the talks and share the videos/slides here asap.
[Note]: There is a Humble Book Bundle (https://www.humblebundle.com/books/data-science-books) (inc. H2O book by Darren)!
Eventbrite Link: https://www.eventbrite.co.uk/e/practical-machine-learning-with-h2o-and-stacknet-tickets-37470398972
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We are back after the summer break. This time we have Darren Cook (the author of Practical Machine Learning with H2O book) and Marios Michailidis (research data scientist at H2O.ai and former Kaggle number one) sharing their experience with us.
Many thanks to our friend Peter Tam, we now have a venue for the meetup. We look forward to seeing you there!
Agenda:
6:00 - 6:30 - Doors open + Pizza
6:30 - 7:15 - Darren's Talk
7:15 - 7:30 - Q & A + Short Break
7:30 - 8:15 - Marios' Talk
8:15 - 9:00 - Q & A + Networking
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Darren's Talk:
Darren will start with an introduction to both H2O and how he found it and settled on it for his company, and how that led to writing a book, and now a video course, about H2O. He will then show a live coding session (in R or Python, by popular vote), which will hopefully be accessible and useful to all levels. He will also delve into a more advanced example of H2O in the last 10 minutes.
Bio:
Darren Cook has over 20 years of experience as a software developer, data analyst, and technical director, working on everything from financial trading systems to NLP, data visualization tools, and PR websites for some of the world's largest brands. He is skilled in a wide range of computer languages, including R, C++, PHP, JavaScript, and Python. He works at QQ Trend, a financial data analysis and data products company. He has written two books for O'Reilly, one on data streaming in HTML5, one on data science with H2O.
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Marios' Talk:
Win machine learning competitions using StackNet (abstract TBA)
Bio: Marios Michailidis is a research data scientist at H2O.ai. He holds a Bsc in accounting Finance from the University of Macedonia in Greece and an Msc in Risk Management from the University of Southampton. He has also nearly finished his PhD in machine learning at University College London (UCL) with a focus on ensemble modelling. He has worked in both marketing and credit sectors in the UK Market and has led many analytics’ projects with various themes including: Acquisition, Retention, Recommenders, Uplift, fraud detection, portfolio optimization and more.
He is the creator of KazAnova(http://www.kazanovaforanalytics.com/), a freeware GUI for credit scoring and data mining 100% made in Java as well as is the creator of StackNet Meta-Modelling Framework (https://github.com/kaz-Anova/StackNet). In his spare time he loves competing on data science challenges and was ranked 1st out of 500,000 members in the popular Kaggle.com data competition platform. Here (http://blog.kaggle.com/2016/02/10/profiling-top-kagglers-kazanova-new-1-in-the-world/) is a blog about Marios being ranked at the top in Kaggle and sharing his knowledge with tricks and ideas.