5 Best Machine Learning Books for beginners in 2021

Best Machine Learning Books

Book 1: Hands-on Machine learning:

Are you looking to become a professional Machine Learning expert with knowledge of Data Science and Deep Learning?

Hands-on Machine Learning with TensorFlow, Scikit Learn and Keras with different tools, Techniques and concepts 2nd edition will be your best book to read.

The advancement in Deep Learning and the development of new tools boosted Machine Learning.

 Even the youngsters who are not having even the knowledge of these technologies are using some simple tools for the implementation of programs by learning from Data.

With the help of some examples, Minimal theory and different python frameworks like Tensorflow, and Scikit Learn, the author helps you to gain knowledge with different topics and tools for easy understanding and build intelligent systems on your own.

On moving with the concepts you will learn some simple techniques by starting with Linear regressions, Processing to Deep neural Networks.

At the end of each chapter, there is an exercise part that helps you implement what you have learnt by doing it in a practical approach.

Concepts you learn from this Best Machine Learning Book:

  • Scikit Learn
  • Vector Machines
  • Support models
  • Decision trees
  • Random forests
  • Ensemble methods
  • Tensorflow Library
  • Neural net Architecture
  • Deep Reinforcement learning
  • Different techniques for scaling deep neural nets

Best for:

Mainly this book is helpful for readers who have knowledge of programming and want to gain practical knowledge.

Pros:

  • Easy to read
  • With exercise on every topic
  • Gain Practical knowledge
  • Can know different techniques and tools
  • Clear images, graphs and tables.
  • Advanced concepts

Cons:

  • Knowledge of programming is a must.
  • Math equations are not pleasant in quality.

Cost: $29.45

Want to buy this book, get it here…

Book 2: Machine Learning Design Patterns:

Most programmers face problems at the time of coding. And these problems can be solved with the help of Design Patterns.

Even if you are working with Machine Learning and you need to solve the problems then design patterns help you a lot.

 Machine Learning Design Pattern books start with What is Machine Learning, Mathematical Aspects, AI frameworks for implementation of these methods.

Build quality Machine Learning systems.

Building blocks, Algorithms like random forests and neural networks, Machine Learning Model Architectures, Model layers like convolutional neural networks, or recurrent neural networks.  

Common patterns covered.

Concepts:

  • Way of identifying the common challenges in coding with ML at the time of evaluating and deploying models.
  • Way of representing data for different Machine Learning model types.
  • How to choose the right model when we face problems.

Best for:

Machine Learning Design Patterns is best for programmers who are having knowledge of ML and also who are willing to know,  how to work with ML when using Google Cloud AI products in your projects.

Pros:

  • Mainly for Programmers, Data Scientists, Data Engineers, and Machine Learning Engineers who want to learn Practical Knowledge on how to use Design Patterns to solve real-world problems.

Cons:

  • Not good for beginners who are not having basic knowledge of Machine Learning.
  • Focused on Google cloud and Tensorflow.

Cost: $35.49

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