Book Review: Hands-on machine learning with Scikit-learn, Keras & TensorFlow

Book Review: Hands-on machine learning with Scikit-learn, Keras & TensorFlow

Hands-on machine learning with Scikit-learn, Keras & TensorFlow is a book that will help you get started with machine learning and deep learning. It will give you a solid foundation in the basics of data science and how to use the tools available in Python. The programming language is becoming increasingly popular for machine learning. This book will walk you through each step of creating a machine learning model.


It is written in simple English that is easy to understand

When learning about a new field, it's easy to become overwhelmed with the technical terms. This book is written in plain English that anyone can follow. If you don't know the underlying concept, it explains it in a straightforward way that even a non-programmer can understand. A machine learning book for beginners should use a simple language anyone can understand.


It explains the problematic concept using common examples that are easy to navigate.

This book will explain the most advanced concepts in machine learning. However, it does this in a way that is easy to follow. If you are not familiar with the term "kernel density estimation," it uses a bright, colourful illustration. If you are not familiar with the word "neural network," it uses a simple, cartoon-like image. If you are not familiar with the term "loss function," it uses an example from sports relatable to anyone. When you're reading a technical book, it's easy to become overwhelmed with the complicated terminology.

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It does not just tell you what to do. It shows you how.

This is one of the most important aspects of any learning resource. When you're learning a new skill, it is beneficial if the author explains the concept and shows you how to do it. When you're learning a new programming language, it's worthwhile if the author describes the concept and offers you a code snippet that you can copy and paste into a programming environment. It shows you how to do it in the form of examples. It is the best way to learn and progress quickly in the field.


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It includes valuable codes you can apply to different projects with an active Github page.

If you want to apply the concept you've learned to other projects, it is beneficial if the author includes helpful code that can help you start. This book contains valuable code for different machine learning projects. It provides code for real-world machine learning projects such as predicting house prices and performing image classification.

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Don't just take my word for it. Try it!

Books can only tell you so much. The best way to learn is by doing. If you want to learn machine learning, you implement machine learning algorithms in your projects. If you want to learn how to use deep learning, implement deep learning algorithms in your projects.

Follow the author's example and implement these algorithms independently.

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Conclusion

Hands-on machine learning with Scikit-learn, Keras & TensorFlow is a valuable book for anyone who wants to learn. It explains the most complex concepts in simple English that anyone can follow. It explains complex concepts using common examples that are easy to navigate. It does not just tell you what to do; it shows you how. And best of all, it includes valuable codes you can apply to different projects with an active Github page. If you want to start machine learning, this book is a must-read.

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