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Here are the The author has explored everything about machine learning and deep learning right from the basics.
The book is written chronologically, in a step-by-step manner.
The Aims and Objectives of the
Here are the target readers for this
You are required to have installed the following on your
The Author guides you on how to install the rest of the Python libraries that are required for machine learning and deep learning.
This book will teach you machine learning classifiers using scikit-learn and tenserflow . The book provides a great overview of functions you can use to build a support vector machine, decision tree, perceptron, and k-nearest neighbors. Thanks of this book you will be able to set up a learning pipeline that handles input and output data, pre-processes it, selects meaningful features, and applies a classifier on it. This book offers a lot of insight into machine learning for both beginners, as well as for professionals, who already use some machine learning techniques. Concepts and the background of these concepts are explained clearly in this tutorial.
This needs proof reading before going to print, the spelling and grammar mistakes are distracting. I also found the book tells me what code snippets are doing rather than why you want to do it and the code itself tells me that much. I think the examples were nice but the instructional content could've been far better, it read a bit like the instructions for Ikea furniture, it tells you to put a in b before c but not why you want to or why the order matters.