Data science is one collective term that is on everyone’s mouth these days, with its applications now being used across big companies, research institutes, and college projects. Since data science is utilised in every sector these days, it is crucial to have a sound knowledge of this vast subject. Although a wide range of information can be found on any search engine, the wiser step is to read materials that have been carefully penned down by experts from the field and are available in the form of e-Books.
In this article, we have composed a list of ten e-Books for beginners that will provide adequate knowledge with regard to data science and big data.
Neural Networks and Deep Learning
Authored by Micheal Nielson, the book is available for free and covers various programming paradigms. The book helps a reader to build neural networks in order to recognize handwritten digits and other use cases. Furthermore, it also lets a reader venture into the space of Deep Learning.
Download the book here.
Think Bayes
When it comes to Data Science, Bayesian Statistics is an important chapter which cannot be avoided at any cost. Penned down by Allen B. Downey, this book makes Bayesian statistics simple to understand for a reader. The book uses Python codes instead of mathematics to keep the readers engaged. Due to this reason, it is advisable to have a decent knowledge of Python before turning through the pages.
Download the book here.
Statistical Learning with Sparsity: The Lasso and Generalizations
Since there has been a wide flow of data in every industry ranging from medical to sports, this book allows a reader to go through a conceptual framework related to ideas about data and data science. The book covers a wide variety of topics such as Algorithms, Multiclass Logistics Regression and Generalized Linear Models.
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The Field Guide of Data Science
‘The Field Guide to Data Science’ has played a crucial role in government and commercial organisations by defining the ideal use of data science. From core concepts of Data Science to going deep into Machine Learning, the book has been put together so that organisations can understand how to use the available data as a resource. With over 15,000+ downloads and available for free, the book contains a number of case studies to highlight its diverse role in multiple scenarios by several organisations.
Download the book here.
The White Book of Data
When it comes to running a business with the help of big data, this book by Fujitsu sheds appropriate light on the hot trending topic. The book takes a reader through the definition of big data, the prevailing challenges existing in the big data space and the approaches in business. It provides guidelines for business analytics and helps in managing business operations. The book educates a reader about clearing hurdles in Big Data to the future and final word on Big Data.
Download the book here.
Machine Learning
Jason Bell has laid down his expertise on the pages of this book, which focuses on helping developers and technical professionals. The book covers a wide variety of topics such as the history of machine learning, their uses and the languages used in machine learning. It also carries a dedicated chapter for decision trees and artificial neural networks.
Download the book here.
Beginners Guide to Analytics
The book is a perfect choice for those who are entering the data analytics space. It provides an array of applications in analytics, ranging from sports to retail. The user is shown new doors to different paid and free tools that are used in the analytics space. Furthermore, the book precisely showcases the future prospect of data analytics, which is vital information for a beginner to know. Through the book, a reader can learn a thing or two about the future of Analytics and the careers related to Analytics.
Download the book here.
Data Science: Theories, Models, Algorithms, and Analytics
In 462 pages, this book provides a bucket full of information regarding Data Science. The book covers a wide variety of sections by giving access to theories, data science algorithms, tools and analytics. Some highlighting contents of the book are Open Source: Modelling in R to Bayes Theorem.
Download the book here.
Automating Boring Stuff with Python
Made for those who love doing practical things, this book teaches everything in a practical way to make learning easy and engaging. The book teaches how to apprehend XLS without using algorithms. Highlighting contents of the book are Automate Trivial using Python and Scraping Data on Web.
Download the book here.
An Introduction to Statistical Learning
Four authors with years of expertise penned down this book for upper-level graduate students to help them enrich their understanding of Statistical Learning. The book contains a number of R Code Labs which could be of great value for a young data scientist who has just entered this wide universe.
Download the book here.
