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The Machine Learning Workshop

You're reading from The Machine Learning Workshop Get ready to develop your own high-performance machine learning algorithms with scikit-learn

Product type Paperback

Published in Jul 2020

Publisher Packt

ISBN-13 9781839219061

Length 286 pages

Edition 2nd Edition

Languages

Python

Tools

Jupyter

Concepts

Machine Learning

Author (1):

Hyatt Saleh

View More author details

Table of Contents (8) Chapters

Preface

1. Introduction to Scikit-Learn

2. Unsupervised Learning – Real-Life Applications FREE CHAPTER

3. Supervised Learning – Key Steps

4. Supervised Learning Algorithms: Predicting Annual Income

5. Supervised Learning – Key Steps

6. Building Your Own Program

Appendix

3. Supervised Learning – Key Steps

Overview

In this chapter, you will learn about key concepts for solving a supervised learning data problem. Starting from splitting the dataset to effectively create unbiased models that perform well on unseen data, you will learn how to measure the performance of the model in order to analyze it and take the necessary actions to improve it. By the end of this chapter, you will have a firm understanding of how to split a dataset, measure a model's performance, and perform error analysis.

The rest of the chapter is locked

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Authors (1)

Hyatt Saleh

Hyatt Saleh

Hyatt Saleh discovered the importance of data analysis for understanding and solving real-life problems after graduating from college as a business administrator. Since then, as a self-taught person, she not only works as a machine learning freelancer for many companies globally, but has also founded an artificial intelligence company that aims to optimize everyday processes. She has also authored Machine Learning Fundamentals, by Packt Publishing.

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