Introduction to Machine Learning with H2O-3 - Part 3

In this tutorial, you will learn how to use H2O's AutoML to solve a classification use case, and a regression use case, we will do this with Python, and also with H2O Flow. 

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Objective
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Select the "Read" button to begin. Explore the main goal of this tutorial
Prerequisites
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Select the "Read" button to begin. Find general information about what you need in order to complete this tutorial
Task 1: Initial Setup
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Select the "Read" button to begin. Import the libraries, estimators, and grid search. Initialize your H2O cluster, and import the dataset
Task 2: Task 2: AutoML Concepts
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Select the "Read" button to begin. Learn about some AutoMLconcepts that will help you get a better understanding of this tutorial
Task 3: Start Experiment
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Select the "Read" button to begin. Explore your dataset, split it and choose your response and predictors
Task 4: H2O AutoML Classification
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Select the "Read" button to begin. Solve the classification problem using H2O's AutoML with Python
Task 5: H2O AutoML Regression
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Select the "Read" button to begin. Solve the regression problem using H2O's AutoML with Python
Task 6: H2O AutoML Classification in Flow
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Select the "Read" button to begin. Solve the classification problem using AutoML in H2O Flow
Task 7: H2O AutoML Regression in Flow
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Select the "Read" button to begin. Solve the regression problem using AutoML in H2O Flow
Task 8: Challenge
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Select the "Read" button to begin. Take on a challenge and see if you can further tune one of the best models from AutoML to get better results
Next Steps
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