Machine Learning with Python: A Step by Step Guide to Learn Machine Learning with Python for Beginners

Walker, Brian

ISBN 10: 1075281512 / ISBN 13: 9781075281518

Editore: Independently published, 2019

All orders ship by next business day! This is a used paperback book. Has moderate wear on cover and/or pages. Has markings on pages. Spine has been opened/creased. Has a personalized note/signature just inside the cover. For USED books, we cannot guarantee supplemental materials such as CDs, DVDs, access codes and other materials. We are a small company and very thankful for your business! Codice articolo 4CNO3H001I7B

Riassunto:

Do you want to learn about machine learning? Are you feeling left out in the rat race where everyone is brushing up on their knowledge in the fields of AI and machine learning? Are you on a time crunch and don’t have enough time or resources to take a formal course on machine learning? If the answer to any of the above questions is yes, then you have chosen the right book.

Throughout the course of this book, you will learn how you can get started with machine learning in Python. This book is a beginner’s guide on the topic of machine learning and will walk you through its different procedures, data composition, and machine training. You will also learn how to build a machine-learning model using various algorithms.

This book will teach you:

• What machine learning is
• The advantages and disadvantages of machine learning
• The algorithms in machine learning
• The different concepts of machine learning
• The types of machine learning
• Why use machine learning in Python
• Data composition on machine learning
• Machine learning applications
• Cleaning data using Python
• Manipulating data in Python using machine learning
• Implementing Machine learning
• And much more

So, what are you waiting for? Grab a copy of this book today and get started on your quest to practicing machine learning.

Dati bibliografici

Titolo: Machine Learning with Python: A Step by Step...
Casa editrice: Independently published
Data di pubblicazione: 2019
Legatura: Brossura
Condizione: Good