Hands-On Training

In the following sections, you'll learn how to get started with H2O via the simple to use Web UI, R, and go through a number of specific examples.

3.1 H2O with Web UI

• Amy Wang: Step-by-step Tutorial (Video Tutorial)

3.2 H2O in R

• Patrick Aboyoun: Basics and Exploratory Data Analysis (EDA)

3.3 Supervised Learning - Regression and Classification

• Patrick Aboyoun: Introduction to Generalized Linear Models in H2O
• Patrick Aboyoun: Introduction to Gradient Boosting Machines in H2O
• Patrick Aboyoun: Introduction to Random Forests in H2O
• Patrick Aboyoun: Regression
• Patrick Aboyoun: Classification
• Arno Candel: Deep Learning

3.4 Unsupervised Learning

• Arno Candel & Spencer Aiello: K-Means Clustering
• Arno Candel: Dimensionality Reduction on MNIST
• Arno Candel: Anomaly Detection on MNIST with H2O Deep Learning

3.5 Advanced Topics

• Arno Candel: Multi-model Parameter Tuning for Higgs Dataset
• Arno Candel: Categorical Feature Engineering for Adult dataset
• Arno Candel: Other Useful Tools

3.6 Yan: Marketing Algorithms and Use-Cases

• Yan Zou: H2O for Marketing/CRM Applications - Presentation
• Yan Zou: H2O for Marketing/CRM Applications - R Script
• Vinod Iyengar: Lead Scoring For Real Time Bidding - Presentation