Automatic and Explainable Machine Learning with H2O
Automatic and Explainable Machine Learning with H2O

Abstract: 

General Data Protection Regulation (GDPR) is now in place. Are you ready to explain your models? This is a hands-on tutorial for beginners. I will demonstrate the use of open-source H2O platform (https://www.h2o.ai/products/h2o/) with both Python and R for automatic and explainable machine learning. Participants will be able to follow and build regression and classification models quickly with H2O AutoML. They will then be able to explain the model outcomes with various methods.

Session Outline
- Building a regression model with H2O AutoML
- Explain results from a regression model with H2O
- Building a classification model with H2O AutoML
- Explain results from a classification model with H2O
- Try it with your own datasets

Background Knowledge
Basic Python or R

Bio: 

Jo-fai (or Joe) has multiple roles (data scientist / evangelist / community manager) at H2O.ai. Since joining the company in 2016, Joe has delivered H2O talks/workshops in 40+ cities around Europe, US, and Asia. Nowadays, he is best known as the H2O #360Selfie guy. He is also the co-organiser of H2O's EMEA meetup groups including London Artificial Intelligence & Deep Learning - one of the biggest data science communities in the world with more than 11,000 members (https://www.meetup.com/London-Artificial-Intelligence-Deep-Learning/).

Open Data Science

Open Data Science
Innovation Center
101 Main St
Cambridge, MA 02142
info@odsc.com

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