Top big data e-books for data scientists that are informative and free!
Big data is just not about digitizing existing information. It also about rendering our lives in data in real-time. Data need to be made available to the public in an understandable form for the correct application context and the right portion so that it becomes knowledgeable and does not harm the privacy and security of others.
With the expansion of the field of big data, there has been a substantial rise in the need for data scientists. Skilled individuals who can leverage the information drawn from the data using big data tools and techniques are needed in the industry. Data scientists need an abundance of knowledge, not just from practical experiences but also by reading different big data books.
Analytics Insight presents a list of the top free big data e-books which can be of immense help for data scientists.
• Data Science and Machine Learning: Mathematical and Statistical Methods
This book provides well-rounded and rigorous information on the mathematics behind modern machine learning techniques. The choice of topic in this book is up-to-date and is perfect for a course on data science for mathematics students at the advanced undergraduate and early graduation levels.
• The Numbers Game Deciphered
This 11-page e-book provides a crisp and concise overview of the world of big data. It begins by setting the context by touching upon the biggest developments in data science. It gives the exact information about who data scientists are and their roles, the history of big data, and much more.
• 8 Essential Concepts of Big Data and Hadoop
This e-book will be a handy guide to understanding the key features of big data and Hadoop. It is a quick primer on the essentials of big data concepts and Hadoop fundamentals that will get the readers up to speed with the details about the one tool that will gain more popularity in the future than any other. This e-book provides a firm foundation in the world of big data and helps navigate through the technology ecosystem easily.
• Python For Everybody
The goal of this book is to provide an informatics-oriented introduction to programming. It puts greater emphasis on using Python to solve data analytics problems in the world of informatics and teaches how to do so by considering the difference in operations between computer science and informatics. This book covers all the concepts, understandably.
• Top Programming Languages For A Data Scientist
This e-book provides a comprehensive overview of the programming languages that aspiring data scientists should learn to build a successful career in the field of big data and data science. For each programming language, like Java, Python, Ruby, SQL, and more, readers will find brief descriptions and the complexities in learning each of these languages.
• Secret to Unlocking Tableau’s Hidden Potential
Tableau makes analytics easy and accessible for not just data analytics but also for top executives like IT professionals, tech business leaders, and everyone in between. It is also recognized as a market leader when it comes to self-service business intelligence. This book provides useful tips, and hacks, and secret techniques to reap the ultimate benefits of using Tableau.
• Ethics of Big Data
This book provides a framework of productive discussion and perspectives about the ethics of big data technologies and business environments. With the increasing size and scope of information that big data offers, it is important to understand the need to maintain ethical practices from a common operational framework. This e-book will guide its readers to understand the importance and implement ethics while using big data for business operations.
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