10 best books on Data Science to boost your Career

mediumThis post was originally published by Gina Andania at Medium [AI]

What are the best books on data science that will update your skill?

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Data Science has become one of the highest-paid and hottest fields in the contemporary market. In the future, data science will continue to grow beyond all the challenges. For now, almost every company has at least a data science position opened. That means, now is the best time to become a data scientist. It’s a crucial time for you to stay updated to stay ahead in the competition and level up your skill to get more senior positions. Since this profession is in high demand, keep educating yourself through the books on data science to get a hold of your data-skills and make it a solid career.

Top Books on Data Science to Read in 2021

You can get a head start right now by reading some of the latest books on data science that are available on Amazon or another marketplace. Here is the list of data science books that you can add to your 2021 reading list and get up to speed on the data science revolution.

1. Step up for Leadership in Enterprise Data Science & Artificial Intelligence with Big Data : Illustrations with R & Python

By: Shitalkumar R Sukhdeve

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Step up for Leadership in Enterprise Data Science & Artificial Intelligence with Big Data : Illustrations with R & Python

The first book on data science that you should read in 2021 is Step up for Leadership in Enterprise Data Science & Artificial Intelligence with Big Data: Illustrations with R & Python. This book will guide you to get the real business scenario and receive the maximum value from the investment in AI. It also helps you to expand the technical skills with R, Python, machine learning with big data as well as business skills, develop a leadership mindset by cutting edge strategies, and bust the myths around data science, AI & big data.

2. Python Data Science Handbook

By: Jake VanderPlas

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Python Data Science Handbook

Recent data shows that Python is still the first leading language for data science and the main tool because of its libraries for storing, manipulating, and gaining insight from data.

This book is the perfect reference for boosting your Python skills including theories about IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools.

3. Advanced R

By: Hadley Wickham

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Advanced R

This book teaches how to use the essential R tools that you need to know, It covers everything from the foundations, including data structures, object-oriented programming, and debugging, to functional programming and performance code.

Advanced R is the perfect book to help you set yourself apart as an R user and immediately make yourself more attractive to potential employers

4. Deep Learning

By: Ian Goodfellow, Yoshua Bengio, and Aaron Courville

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Deep Learning

Deep Learning is the best reference for learning algorithms. The most feature that makes deep learning so powerful is just because It automates feature discovery.

This book doesn’t contain much code but has good insights about how to approach problems with machine learning.

Having some experience in deep learning can help you to get a new career opportunity in big companies like Google, Facebook, and Amazon that need expertise in deep learning.

5. Think Stats

By: Allen B. Downey

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Think Stats

Machine learning models are rooted in the fundamentals of probability theory. As a data scientist, having a solid grasp of probability and statistics is an important skill that you must have.

Think Bayes is geared towards programmers, the book follows the computational approach rather than the traditional mathematical approach. The goal behind this book is to introduce the practical tools for exploratory data analysis and follow a new style of data processing.

6. Data Science for Dummies

By: Lillian Pierson

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Data Science for Dummies

Data Science for Dummies is one of the best introductory textbooks for entering the data science field as a professional.

This book focuses more on the business side of data science. It covers the basics that beginners need to know as a data scientist, including MPP platforms, Spark, machine learning, NoSQL, Hadoop, big data analytics, MapReduce, and AI.

The book also explores broad overviews of topics like data engineering and programming languages.

7. Build a Career in Data Science

By: Emily Robinson and Jacqueline Nolis

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Build a Career in Data Science

This book will be your companion in landing your first data science job and preparing for a professional career.

The idea behind this book is to help the beginner understand the lifecycle of a typical data science project, how to adapt to company needs, how to prepare for a management role, and even tips to help you manage difficult stakeholders.

8. Data Science from Scratch: First Principles of Python

By: Joel Grus

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Data Science from Scratch: First Principles of Python

This book starts with the very fundamentals of the tools that make Data Science possible. We’ll learn how algorithms work by implementing them from scratch. The idea behind this book is to tell how the various algorithms, libraries, frameworks, and other toolkits in general, work in Data Science

9. Think Python Data Science for Business

By: Foster Provost and Tom Fawcett

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Think Python Data Science for Business

This book is written by data science experts to introduce the fundamentals of data science through data analytic thinking and also helps you to get knowledge about business value from the data. This guide makes you understand the many data-mining techniques in use today. The book also provides many examples of real-world business problems to illustrate these principles.

10. A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills

By: by Jay Wengrow

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A Common-Sense Guide to Data Structures and Algorithms: Level Up Your Core Programming Skills

This book helps you to learn how to use hash tables, trees, and graphs to improve the efficiency of your code. It serves you the topic about how to mastering these concepts that make your code run faster and more efficiently.

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This post was originally published by Gina Andania at Medium [AI]

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