Subscription

0
You have no products in your basket yet

Save more on your purchases!
Savings automatically calculated. No voucher code required

eBook

Print

$54.99
Subscription

$15.99
Monthly
eBook

Print

$54.99
Subscription

$15.99
Monthly
Download this book in **EPUB** and **PDF** formats

Access this title in our online reader with advanced features

- Get started in the field of Machine Learning with the help of this solid, concept-rich, yet highly practical guide.
- Your one-stop solution for everything that matters in mastering the whats and whys of Machine Learning algorithms and their implementation.
- Get a solid foundation for your entry into Machine Learning by strengthening your roots (algorithms) with this comprehensive guide.

In this book, you will learn all the important machine learning algorithms that are commonly used in the field of data science. These algorithms can be used for supervised as well as unsupervised learning, reinforcement learning, and semi-supervised learning. The algorithms that are covered in this book are linear regression, logistic regression, SVM, naïve Bayes, k-means, random forest, TensorFlow and feature engineering.
In this book, you will how to use these algorithms to resolve your problems, and how they work. This book will also introduce you to natural language processing and recommendation systems, which help you to run multiple algorithms simultaneously.
On completion of the book, you will know how to pick the right machine learning algorithm for clustering, classification, or regression for your problem

[*] Acquaint yourself with the important elements of machine learning
[*] Understand the feature selection and feature engineering processes
[*] Assess performance and error trade-offs for linear regression
[*] Build a data model and understand how it
[*] Learn to tune the parameters of SVMs
[*] Implement clusters in a dataset
[*] Explore the concept of Natural Processing Language and Recommendation Systems
[*] Create a machine learning architecture from scratch

Download this book in **EPUB** and **PDF** formats

Access this title in our online reader with advanced features

Publication date :
Jul 24, 2017

Length
360 pages

Edition :
1st Edition

Language :
English

ISBN-13 :
9781785889622

Category :

Languages :

Concepts :

Title Page

Credits

About the Author

About the Reviewers

www.PacktPub.com

Customer Feedback

Preface

1. A Gentle Introduction to Machine Learning

2. Important Elements in Machine Learning

3. Feature Selection and Feature Engineering

4. Linear Regression

5. Logistic Regression

6. Naive Bayes

7. Support Vector Machines

8. Decision Trees and Ensemble Learning

9. Clustering Fundamentals

10. Hierarchical Clustering

11. Introduction to Recommendation Systems

12. Introduction to Natural Language Processing

13. Topic Modeling and Sentiment Analysis in NLP

14. A Brief Introduction to Deep Learning and TensorFlow

15. Creating a Machine Learning Architecture

Filter

No reviews found

How do I buy and download an eBook?

How can I make a purchase on your website?

Where can I access support around an eBook?

What eBook formats do Packt support?

What are the benefits of eBooks?

What is an eBook?