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The Data Science Workshop

You're reading from   The Data Science Workshop Learn how you can build machine learning models and create your own real-world data science projects

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Product type Paperback
Published in Aug 2020
Publisher Packt
ISBN-13 9781800566927
Length 824 pages
Edition 2nd Edition
Languages
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Authors (5):
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Robert Thas John Robert Thas John
Author Profile Icon Robert Thas John
Robert Thas John
Thomas Joseph Thomas Joseph
Author Profile Icon Thomas Joseph
Thomas Joseph
Anthony So Anthony So
Author Profile Icon Anthony So
Anthony So
Dr. Samuel Asare Dr. Samuel Asare
Author Profile Icon Dr. Samuel Asare
Dr. Samuel Asare
Andrew Worsley Andrew Worsley
Author Profile Icon Andrew Worsley
Andrew Worsley
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Toc

Table of Contents (16) Chapters Close

Preface
1. Introduction to Data Science in Python 2. Regression FREE CHAPTER 3. Binary Classification 4. Multiclass Classification with RandomForest 5. Performing Your First Cluster Analysis 6. How to Assess Performance 7. The Generalization of Machine Learning Models 8. Hyperparameter Tuning 9. Interpreting a Machine Learning Model 10. Analyzing a Dataset 11. Data Preparation 12. Feature Engineering 13. Imbalanced Datasets 14. Dimensionality Reduction 15. Ensemble Learning

Introduction

Welcome to the fascinating world of data science! We are sure you must be pretty excited to start your journey and learn interesting and exciting techniques and algorithms. This is exactly what this book is intended for.

But before diving into it, let's define what data science is: it is a combination of multiple disciplines, including business, statistics, and programming, that intends to extract meaningful insights from data by running controlled experiments similar to scientific research.

The objective of any data science project is to derive valuable knowledge for the business from data in order to make better decisions. It is the responsibility of data scientists to define the goals to be achieved for a project. This requires business knowledge and expertise. In this book, you will be exposed to some examples of data science tasks from real-world datasets.

Statistics is a mathematical field used for analyzing and finding patterns from data. A lot of...

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