Jo-fai Chow

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Jo-fai (Joe) is a data scientist at H2O.ai. Before joining H2O, he was in the business intelligence team at Virgin Media where he developed data products to enable quick and smart business decisions. He also worked remotely for Domino Data Lab as a data science evangelist promoting products via blogging and giving talks at external events. Joe has a background in water engineering. Before his data science journey, he was an EngD researcher at STREAM Industrial Doctorate Centre working on machine learning techniques for drainage design optimization. Prior to that, he was an asset management consultant specialized in data mining and constrained optimization for the utilities sector in UK ...

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Activity
About

Jo-fai Chow

Presentations

A Systematic, Multi-Criteria Decision Support Framework for Sustainable Drainage Design

Udacity Statement (Introduction to Statistics, August 2012)

Developing a New Decision Support System for SuDS

Designing Sustainable Drainage Systems

A Systematic, Multi-Criteria Decision Support Framework for Sustainable Drainage Design

Deploying your Predictive Models as a Service via Domino

Kaggle competitions, new friends, new skills and new opportunities

Improving Model Predictions via Stacking and Hyper-parameters Tuning

Introduction to Generalised Low-Rank Model and Missing Values

Using H2O Random Grid Search for Hyper-parameters Optimization

Kaggle Competitions, New Friends, New Skills and New Opportunities

H2O Machine Learning Use Cases

Project "Deep Water"

H2O Deep Water - Making Deep Learning Accessible to Everyone

H2O Deep Water - Making Deep Learning Accessible to Everyone

From Kaggle to H2O - The True Story of a Civil Engineer Turned Data Geek

Introduction to Machine Learning with H2O and Python

Introduction to Machine Learning with H2O and Python

H2O at Poznan R Meetup

Introduction to H2O and Model Stacking Use Cases

H2O at BelgradeR Meetup

H2O at Berlin R Meetup

Automatic and Interpretable Machine Learning with H2O and LIME

Automatic and Interpretable Machine Learning in R with H2O and LIME

Making Multimillion-Dollar Baseball Decisions with H2O AutoML, LIME and Shiny

Documents

Coursera Statement (Data Analysis, Mar 2013)

Coursera Statement (Computing for Data Analysis, Oct 2013)

Coursera Statement (Computational Investing, Part I,