Machine Learning - A Comprehensive, Step-by-Step Guide to Learning and Applying Advanced Concepts and Techniques in Machine Learning

Do you have a clear understanding of the different types of machine learning algorithms?

Do you know what a neural network is, and how you can build it?

If you have read the second book in the series, the answer to both the questions is yes. If you want to gather more information about machine learning, deep learning and neural networks, you have come to the right place.

Over the course of the book, you will gather information on the following:

• The difference between machine learning and deep learning

• Python libraries

• Advantages of using Python

• Developing supervised and unsupervised machine learning algorithms in Python

• Assessing or evaluating a neural network

The information in this book will help you gather a clear understanding of what machine learning is, how you can build different models and where you can use these models. You can use the programs given in the book as a sample or a base for you to build your programs. If you are still learning how to code in Python, you can simply copy the code in the books and analyze different input data sets.

So what are you waiting for? Grab a copy of this book Now, and build your very own regression and clustering machine learning algorithms.