Awesome H2O

Below is a curated list of all the awesome projects, applications, research, tutorials, courses and books that use H2O, an open source, distributed machine learning platform. H2O offers parallelized implementations of many supervised and unsupervised machine learning algorithms such as Generalized Linear Models, Gradient Boosting Machines (including XGBoost), Random Forests, Deep Neural Networks (Deep Learning), Stacked Ensembles, Naive Bayes, Cox Proportional Hazards, K-means, PCA, Word2Vec, as well as a fully automatic machine learning algorithm (AutoML).

H2O.ai produces many tutorials, blog posts, presentations and videos about H2O, but the list below is comprised of awesome content produced by the greater H2O user community.

We are just getting started with this list, so pull requests are very much appreciated! 🙏 Please review the contribution guidelines before making a pull request. If you're not a GitHub user and want to make a contribution, please send an email to [email protected].

If you think H2O is awesome too, please ⭐ the H2O GitHub repository.

Contents

• Blog Posts & Tutorials
• Books
• Research Papers
• Benchmarks
• Presentations
• Courses
• Software (built using H2O)
• License

Blog Posts & Tutorials

• Using H2O AutoML to simplify training process (and also predict wine quality) Aug 4, 2020
• Visualizing ML Models with LIME
• Parallel Grid Search in H2O Jan 17, 2020
• Importing, Inspecting and Scoring with MOJO models inside H2O Dec 10, 2019
• Artificial Intelligence Made Easy with H2O.ai: A Comprehensive Guide to Modeling with H2O.ai and AutoML in Python June 12, 2019
• Anomaly Detection With Isolation Forests Using H2O Dec 03, 2018
• Predicting residential property prices in Bratislava using recipes - H2O Machine learning Nov 25, 2018
• Inspecting Decision Trees in H2O Nov 07, 2018
• Gentle Introduction to AutoML from H2O.ai Sep 13, 2018
• Machine Learning With H2O — Hands-On Guide for Data Scientists Jun 27, 2018
• Using machine learning with LIME to understand employee churn June 25, 2018
• Analytics at Scale: h2o, Apache Spark and R on AWS EMR June 21, 2018
• Automated and unmysterious machine learning in cancer detection Nov 7, 2017
• Time series machine learning with h2o+timetk Oct 28, 2017
• Sales Analytics: How to use machine learning to predict and optimize product backorders Oct 16, 2017
• HR Analytics: Using machine learning to predict employee turnover Sep 18, 2017
• Autoencoders and anomaly detection with machine learning in fraud analytics May 1, 2017
• Building deep neural nets with h2o and rsparkling that predict arrhythmia of the heart Feb 27, 2017
• Predicting food preferences with sparklyr (machine learning) Feb 19, 2017
• Moving largish data from R to H2O - spam detection with Enron emails Feb 18, 2016