HyperOpt for Automated Machine Learning With Scikit-Learn

Automated Machine Learning (AutoML) refers to techniques for automatically discovering well-performing models for predictive modeling tasks with very little user involvement.

HyperOpt is an open-source library for large scale AutoML and HyperOpt-Sklearn is a wrapper for HyperOpt that supports AutoML with HyperOpt for the popular Scikit-Learn machine learning library, including the suite of data preparation transforms and classification and regression algorithms.

In this tutorial, you will discover how to use HyperOpt for automatic machine learning with Scikit-Learn in Python.

After completing this tutorial, you will know:

• Hyperopt-Sklearn is an open-source library for AutoML with scikit-learn data preparation and machine learning models.
• How to use Hyperopt-Sklearn to automatically discover top-performing models for classification tasks.
• How to use Hyperopt-Sklearn to automatically discover top-performing models for regression tasks.

Let’s get started.

HyperOpt for Automated Machine Learning With Scikit-Learn
Photo by Neil Williamson, some rights reserved.

Tutorial Overview

This tutorial is divided into four parts; they are:

1. HyperOpt and HyperOpt-Sklearn
2. How to Install and Use HyperOpt-Sklearn
3. HyperOpt-Sklearn for Classification
4. HyperOpt-Sklearn for Regression

HyperOpt

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