The Supervised Learning Workshop: A New,Interactive Approach to Understanding Supervised Learning Algorithms,2nd Edition
by Blaine Bateman,Ashish Ranjan Jha,Benjamin Johnston,Ishita Mathur
Print Length 页数: 490 pages
Publisher finelybook 出版社: Packt Publishing (February 28,2020)
Language 语言: English
ISBN-10: 1800209045
ISBN-13: 9781800209046
Book Description
Cut through the noise and get real results with a step-by-step approach to understanding supervised learning algorithms
You already know you want to understand supervised learning,and a smarter way to do that is to learn by: doing. The Supervised Learning Workshop focuses on building up your practical skills so that you can deploy and build solutions that leverage key supervised learning algorithms. You’ll learn from real examples that lead to real results.
Throughout The Supervised Learning Workshop,you’ll take an engaging step-by-step approach to understand supervised learning. You won’t have to sit through any unnecessary theory. If you’re short on time you can jump into a single exercise each day or spend an entire weekend learning how to predict future values with auto regressors. It’s your choice. Learning on your terms,you’ll build up and reinforce key skills in a way that feels rewarding.
Every physical print copy of The Supervised Learning Workshop unlocks access to the interactive edition. With videos detailing all exercises and activities,you’ll always have a guided solution. You can also benchmark yourself against assessments,track progress,and receive content updates. You’ll even earn a secure credential that you can share and verify online upon completion. It’s a premium learning experience that’s included with your printed copy. To redeem,follow the instructions located at the start of your book.
Fast-paced and direct,The Supervised Learning Workshop is the ideal companion for those with some Python background who are getting started with machine learning. You’ll learn how to apply key algorithms like a data scientist,learning along the way. This process means that you’ll find that your new skills stick,embedded as best practice. A solid foundation for the years ahead.
What you will learn
Get to grips with the fundamental of supervised learning algorithms
Discover how to use Python libraries for supervised learning
Learn how to load a dataset in pandas for testing
Use different types of plots to visually represent the data
Distinguish between regression and classification problems
Learn how to perform classification using K-NN and decision trees
Contents
Preface
Chapter 1: Fundamentals of Supervised Learning Algorithms
Chapter 2: Exploratory Data Analysis and Visualization
Chapter 3: Linear Regression
Chapter 4: Autoregression
Chapter 5: Classification Techniques
Chapter 6: Ensemble Modeling
Chapter 7: Model Evaluation
Appendix
Index
