Jo-fai Chow

43 Seguidores

28 SlideShares 43 Seguidores 4 Siguiendos

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 ...

h2o machine learning h2o.ai deep learning introduction open source caffè mxnet tensorflow conference kaggle python gpu platform r meetup coursera drainage design decision making use case tutorial data science london career predictive models dss suds udacity data analysis sustainability poster evaluation mlb baseball workshop lime model stacking iot code pydata skills tools integration company profiles animals web service domino data lab sustainable drainage decision support system perugia exeter hamburg statistics artificial intelligence conferences confer resear sustainable development

Presentaciones
Documentos
Infografías

Más reciente Más populares

Jo-fai Chow

Deploying your Predictive Models as a Service via Domino

Automatic and Interpretable Machine Learning with H2O and LIME

Using H2O Random Grid Search for Hyper-parameters Optimization

Introduction to Generalised Low-Rank Model and Missing Values

Designing Sustainable Drainage Systems

Improving Model Predictions via Stacking and Hyper-parameters Tuning

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

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

Project "Deep Water"

H2O Machine Learning Use Cases

Developing a New Decision Support System for SuDS

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

Introduction to H2O and Model Stacking Use Cases

H2O Deep Water - Making Deep Learning Accessible to Everyone

Kaggle competitions, new friends, new skills and new opportunities

Introduction to Machine Learning with H2O and Python

H2O at Poznan R Meetup

Introduction to Machine Learning with H2O and Python

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

H2O Deep Water - Making Deep Learning Accessible to Everyone