Python Machine Learning: A Step-by-Step Guide to Scikit-Learn and TensorFlow (Includes a Python Programming Crash Course)

✍ Scribed by Konnor Cluster

• Year: 2020
• Tongue: English
• Leaves: 90
• Category: Library

✦ Synopsis

If you need to learn how to use the Python Programming Language to implement your own Machine Learning solution, and you are searching for a reference to start from, then keep reading.

Machine learning represents now the most interesting, performing and growing technology among all technologies related to Artificial Intelligence and represents also an incredible opportunity if you want to grow your business or if you are searching for a new job, but it’s not very easy to understand how it works. Sometimes, even the most seasoned and skilled engineers are scared to approach this new topic.

This book can assist you in understanding 

• How machine learning works 
• How to work with Python
• How to set up and run a machine learning solution on your home computer
• How to use two of the most popular Machine Learning libraries  

Even if you have not a degree in computer science or math, even if you have never worked with Machine Learning or Python, with this book you can understand how to benefit from this set of technologies and unlock their extraordinary potential. 
If you want to enter into the exciting world of Machine Learning, scroll up and click the "buy now" button!

✦ Table of Contents

Python Machine Learning
Table of Contents
Introduction
Part 1: An Introduction to Machine Learning
Chapter 1: What is Machine Learning
Chapter 2: The Different Types of Machine Learning
Chapter 3: How Does Machine Learning Compare to AI
Part 2: Your Python Crash Course
Chapter 4: What is Python and How to Set It Up On Your Computer?
Chapter 5: Some of the Basic Parts of Your Code
Chapter 6: How to Write Your Own Conditional Statements
Chapter 7: OOP and Functions
Chapter 8: How to Raise and Manage Your Own Exceptions in the Code
Part 3: What is Scikit-Learn?
Chapter 9: What is Scikit-Learn?
Chapter 10: Supervised Learning with Scikit-Learn
Chapter 11: Unsupervised Machine Learning with Scikit-Learn
Part 4: The TensorFlow Library
Chapter 12: What is the TensorFlow Library
Chapter 13: Working with the High-Level APIs
Chapter 14: The Estimators in TensorFlow
Chapter 15: Understanding the Low-Level APIs
Conclusion