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Automatic Machine Learning with H2O AutoML and Python
  • Level Intermediate
  • Duration 2 hours
  • Offered by

About

This is a hands-on, guided project on Automatic Machine Learning with H2O AutoML and Python. By the end of this project, you will be able to describe what AutoML is and apply automatic machine learning to a business analytics problem with the H2O AutoML interface in Python. H2O's AutoML automates the process of training and tuning a large selection of models, allowing the user to focus on other aspects of the data science and machine learning pipeline such as data pre-processing, feature engineering and model deployment. To successfully complete the project, we recommend that you have prior experience in Python programming, basic machine learning theory, and have trained ML models with a library such as scikit-learn. We will not be exploring how any particular model works nor dive into the math behind them. Instead, we assume you have this foundational knowledge and want to learn to use H2O's AutoML interface for automatic machine learning. Note: This course works best for learners who are based in the North America region. We're currently working on providing the same experience in other regions.

Auto Summary

Explore the exciting world of Automatic Machine Learning with H2O AutoML and Python in this hands-on, guided project designed for data science and AI enthusiasts. Led by Coursera, this professional-level course spans 120 minutes and delves into automating model training and tuning, allowing you to focus on data pre-processing, feature engineering, and deployment. Ideal for learners with Python programming and basic ML experience, the course is available through a Starter subscription, primarily targeting those in North America.