The Elements of Statistical Learning - Another valuable statistics text that covers just about everything you might want to know, and then some (it's over 750 pages long). Make sure you get the most updated version of the book from here (as of this writing, that's the 2017 edition). Data Mining and Analysis - This Cambridge University Press text will take you deep into the statistics and algorithms used for various types of data analysis. Do you need books to learn data science?
This book introduces probability, statistics and stochastic processes to students. It can be used by both students and practitioners in engineering, various sciences, finance, and other related fields. It provides a clear and intuitive approach to these topics while maintaining mathematical accuracy. You can also find courses and videos online.
This post is part of "AI education", a series of posts that review and explore educational content on data science and machine learning. But with so many educational books, video tutorials and online courses on data science and machine learning, finding the right starting point can be quite confusing. Readers often ask me for advice on the best roadmap for becoming a data scientist. To be frank, there's no one-size-fits-all approach, and it all depends on the skills you already have. In this post, I will review three very good introductory books on data science and machine learning.
Our editors have compiled this directory of the best Python books based on Amazon user reviews, rating, and ability to add business value. There are loads of free resources available online (such as Solutions Review's Data Analytics Software Buyer's Guide, visual comparison matrix, and best practices section) and those are great, but sometimes it's best to do things the old fashioned way. There are few resources that can match the in-depth, comprehensive detail of one of the best Power BI books. The editors at Solutions Review have done much of the work for you, curating this comprehensive directory of the best Python books on Amazon. Titles have been selected based on the total number and quality of reader user reviews and ability to add business value. Each of the books listed in the first section of this compilation have met a minimum criteria of 15 reviews and a 4-star-or-better ranking. Below you will find a library of titles from recognized industry analysts, experienced practitioners, and subject matter experts spanning the depths of Python coding for beginners all the way to advanced data science best practices for Python users. This compilation includes publications for practitioners of all skill levels. "Python Crash Course is the world's best-selling guide to the Python programming language. In the first half of the book, you'll learn basic programming concepts, such as variables, lists, classes, and loops, and practice writing clean code with exercises for each topic. You'll also learn how to make your programs interactive and test your code safely before adding it to a project. In the second half, you'll put your new knowledge into practice with three substantial projects: a Space Invaders-inspired arcade game, a set of data visualizations with Python's handy libraries, and a simple web app you can deploy online."
Python is one of the most widely used programming languages in the data science field. Python has many packages and libraries that are specifically tailored for certain functions, including pandas, NumPy, scikit-learn, Matplotlib, and SciPy. So if you are looking for the Best Books on Data Science with Python, then you should check these books. In this article, you will find 8 Best Books on Data Science with Python. These books will give you in-depth knowledge starting from basics to advanced level.