5 Data Science Books You Must Read

Source: Deep Learning on Medium

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  1. Artificial Intelligence: A Modern Approach

The book provides a comprehensive introduction to various fields of artificial intelligence and therefore is suitable for readers who approach artificial intelligence for the first time and for readers who want to explore varying fields of AI.

2. Python Machine Learning: Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow, 2nd Edition

The book introduces each machine learning concepts in details and provides code examples with python which are well explained.

3. Hands-On Machine Learning with Scikit-Learn and TensorFlow: Concepts, Tools, and Techniques to Build Intelligent Systems

The book provides a comprehensive instructions for readers on topics including machine learning, deep learning and step by step code examples using both scikit-learn and tensorflow.

4. Data Mining: Concepts and Techniques (The Morgan Kaufmann Series in Data Management Systems)

The book introduces various methods used in data mining and is suitable to be used as introduction materials for data mining.

5. Deep Learning (Adaptive Computation and Machine Learning series)

The book is regarded as the “Bible” of Deep Learning. It includes two parts: the first part provides a brief overview of topics that should be known before studying deep learning such as linear algebra, numerical analysis and machine learning, and the second part concentrates on various concepts and topics on deep learning. This book should be read for everybody who wants to study deep learning.