Machine Learning With Scikit-learn Quick Start Guide

About Machine Learning With Scikit-learn Quick Start Guide

Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering.

Key Features

Build your first machine learning model using scikit-learn
Train supervised and unsupervised models using popular techniques such as classification, regression and clustering
Understand how scikit-learn can be applied to different types of machine learning problems

Book Description

Scikit-learn is a robust machine learning library for the Python programming language. It provides a set of supervised and unsupervised learning algorithms. This book is the easiest way to learn how to deploy, optimize, and evaluate all of the important machine learning algorithms that scikit-learn provides.

This book teaches you how to use scikit-learn for machine learning. You will start by setting up and configuring your machine learning environment with scikit-learn. To put scikit-learn to use, you will learn how to implement various supervised and unsupervised machine learning models. You will learn classification, regression, and clustering techniques to work with different types of datasets and train your models.

Finally, you will learn about an effective pipeline to help you build a machine learning project from scratch. By the end of this book, you will be confident in building your own machine learning models for accurate predictions.

Learn how to work with all scikit-learn's machine learning algorithms
Install and set up scikit-learn to build your first machine learning model
Employ Unsupervised Machine Learning Algorithms to cluster unlabelled data into groups
Perform classification and regression machine learning
Use an effective pipeline to build a machine learning project from scratch

Website	https://amzn.to/3fqi9Sw
Employees	11-50 employees View all Machine Learning With Scikit-learn Quick Start Guide employees
Industry	E-learning
Founded	2018
Keywords	Programming, E-Learning, Data Science, Machine Learning