Distributed Machine Learning and Its Implementation with H2O

Build distributed, fast, and scalable models with H2O, an end-to-end ML framework widely used for fraud risk, churn, advertising, and healthcare analytics.

Advanced

37 Lessons

Certificate of Completion

Build distributed, fast, and scalable models with H2O, an end-to-end ML framework widely used for fraud risk, churn, advertising, and healthcare analytics.

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

72 Playgrounds

6 Quizzes

This course includes

72 Playgrounds

6 Quizzes

Course Overview

This course teaches about a distributed and highly scalable machine learning framework known as H2O-3. H2O has become the go-to solution for organizations seeking to build data-driven and explainable solutions. In this course, you’ll learn about H2O’s versatile machine learning framework, which empowers you with high-performing and interpretable machine learning models. The H2O framework is compatible with Java, JSON, R, Python, and Scala. You’ll start by covering the concepts of machine learning models. ...Show More

TAKEAWAY SKILLS

Machine Learning

Data Science

Python

Artificial Intelligence

What You'll Learn

An understanding of distributed machine learning

Working knowledge of the powerful H2O ML framework, including various algorithms and their implementation in data science use cases

Hands-on experience in building explainable machine learning models and deriving insights from them

The ability to utilize autoML tools effectively for building fast, scalable, and robust machine learning models

What You'll Learn

An understanding of distributed machine learning

Course Content

Introduction to Machine Learning

Let’s Dive In

Machine Learning Concepts Evaluating Machine Learning Models Machine Learning Frameworks Quiz: Machine Learning Concepts

Supervised Learning: Regression Models with H2O

Regression with H2O Exploratory Data Analysis Setting Up the H2O Cluster Regression Model and Prediction Regression Model Explanation Challenge: Improve H2OXGBoost Regression Model Solution: Improve H2OXGBoost Regression Model Quiz: H2O Regression Concepts

Supervised Learning: Classification Models with H2O

Classification with H2O Exploratory Data Analysis Setting Up the H2O Cluster H2O AutoML Is All You Need Classification Model and Prediction Model Tuning with H2O Grid Search Classification Model Explanation Challenge: Classifier Model Feature Engineering Solution: Classifier Model Feature Engineering Quiz: H2O Classification Concepts

Unsupervised Learning: Clustering with H2O

Clustering with H2O Exploratory Data Analysis Clustering Model and Prediction Challenge: Analyzing Clusters Solution: Analyzing Clusters Quiz: H2O Clustering Concepts

Unsupervised Learning: Anomaly Detection with H2O

Anomaly Detection with H2O Anomaly Detection Model and Prediction Interpreting H2O Isolation Forest Model Challenge: Interpreting Anomalies Solution: Interpreting Anomalies Quiz: H2O Anomaly Detection Model

Closing Notes

1 Lesson

Appendix

1 Lesson

Course Author

Trusted by 1.4 million developers working at companies

Anthony Walker

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Emma Bostian 🐞

@EmmaBostian

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

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