Auto-Sklearn for Automated Machine Learning in Python
Last Updated on September 12, 2020
Automated Machine Learning (AutoML) refers to techniques for automatically discovering well-performing models for predictive modeling tasks with very little user involvement.
Auto-Sklearn is an open-source library for performing AutoML in Python. It makes use of the popular Scikit-Learn machine learning library for data transforms and machine learning algorithms and uses a Bayesian Optimization search procedure to efficiently discover a top-performing model pipeline for a given dataset.
In this tutorial, you will discover how to use Auto-Sklearn for AutoML with Scikit-Learn machine learning algorithms in Python.
After completing this tutorial, you will know:
- Auto-Sklearn is an open-source library for AutoML with scikit-learn data preparation and machine learning models.
- How to use Auto-Sklearn to automatically discover top-performing models for classification tasks.
- How to use Auto-Sklearn to automatically discover top-performing models for regression tasks.
Let’s get started.
Auto-Sklearn for Automated Machine Learning in Python
Photo by Richard, some rights reserved.
Tutorial Overview
This tutorial is divided into four parts; they are:
- AutoML With Auto-Sklearn
- Install