{"id":12049,"date":"2024-05-06T18:57:29","date_gmt":"2024-05-06T13:27:29","guid":{"rendered":"http:\/\/ivyproschool.com\/blog\/?p=12049"},"modified":"2024-05-06T19:05:06","modified_gmt":"2024-05-06T13:35:06","slug":"best-data-science-books","status":"publish","type":"post","link":"https:\/\/ivyproschool.com\/blog\/best-data-science-books\/","title":{"rendered":"8 Best Data Science Books You Must Read"},"content":{"rendered":"\t\t
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Mastering data science requires constant learning. Books can help you learn new things, improve your techniques, and change how you approach problems.<\/p>

No matter whether you are an aspiring data scientist or a professional, reading data science books lets you effectively transform raw data into powerful insights and tell better stories.\u00a0<\/p>

To help you on this journey, in this post, we have shared some of the best data science books you must read. So, get ready to become smarter and more skilled.\u00a0<\/p>

\u00a0<\/p>

8 Data Science Books that Will Make You Smarter<\/b><\/h2>

Here are some of the best books for data scientists that will help you sharpen your skills. They will improve your problem-solving ability and help you use data to make sense of this confusing world:<\/p>

1. Data Science from Scratch: First Principles with Python<\/b><\/h3>

Author:<\/b> Joel Grus is a research engineer at the Allen Institute for Artificial Intelligence. Formerly a software engineer at Google and a data scientist at numerous startups.<\/p>

About: <\/b>This is one of the best data science books for beginners that goes beyond using basic tools. The book covers data manipulation, machine learning models, and even advanced topics like recommendation systems and natural language processing. You will gain a strong foundation in the math and statistics behind data science, plus the coding skills to put it into practice.<\/p>

Get the book:<\/b> Data Science from Scratch<\/a><\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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2. Data Science for Business: What You Need to Know about Data Mining and Data-Analytic\u00a0<\/b>Thinking<\/b><\/h3>

Authors: <\/b>It\u2019s written by famous data science experts Foster Provost and Tom Fawcett. Provost is a Professor of Data Science at New York University\u2019s Stern School of Business. And Fawcett is a machine learning Ph.D. holder who has worked in industry R&D for over 20 years.<\/p>

About: <\/b>This book teaches you the core concepts of data science and how to apply them to solve real business problems. The book emphasizes \u201cdata-analytic thinking\u201d to help you extract valuable insights from data. It\u2019s ideal for those wanting to bridge the gap between data science and its practical business applications.<\/p>

Get the book: <\/b>Data Science for Business<\/a><\/p>

\u00a0<\/p>

3. Python for Data Analysis<\/b><\/h3>

Author:<\/b> Wes McKinney is an American software developer, Co-founder of Voltron Data, and creator of the Python pandas project. He studied theoretical mathematics at MIT and graduated in 2006.<\/p>

About:<\/b> This data science book teaches you essential Python skills for working with data. You will learn data cleaning, manipulation, and analysis to effectively solve diverse sets of data analysis problems. This book is packed with practical case studies and is perfect if you are new to Python and want to get introduced to scientific computing in Python.\u00a0<\/p>

Get the book: <\/b>Python for Data Analysis<\/a><\/p>

\u00a0<\/p>

4. Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python<\/b><\/h3>

Authors:<\/b> It\u2019s written by Peter Bruce and Andrew Bruce. Peter Bruce is the founder of the Institute for Statistics Education at Statistics.com. Andrew Bruce is a Ph.D. holder in statistics at the University of Washington and has 30+ years of experience in statistics and data science.\u00a0<\/p>

About:<\/b> This book bridges the gap between traditional statistics and how it\u2019s used in data science<\/a>. It covers essential statistical methods, shows how to apply them correctly, and helps you avoid common mistakes. You will learn about exploratory analysis, sampling, experimental design, regression, classification, and even machine learning from a statistical viewpoint.<\/p>

Get the book: <\/b>Practical Statistics for Data Scientists<\/a><\/p>

\u00a0<\/h3>

5. Storytelling with Data: A Data Visualization Guide for Business Professionals<\/b><\/h3>

Author:<\/b> Cole Nussbaumer Knaflic is the founder and CEO of Storytelling With Data. She has been analyzing data and telling compelling stories for the last 10 years.<\/p>

About:<\/b> \u201cStorytelling with Data\u201d is a must-read book for data scientists. It teaches you how to transform data into clear and compelling visuals that tell an informative story. You will learn the principles of effective data visualization and how to go beyond basic charts to create presentations that engage your audience. If you want to make your data analysis truly impactful, this book is for you.\u00a0<\/p>

Get the book: <\/b>Storytelling with Data<\/a><\/p>

\u00a0<\/p>

6. R for Data Science: Import, Tidy, Transform, Visualize, and Model Data<\/b><\/h3>

Authors:<\/b> It\u2019s written by Hadley Wickham and Garrett Grolemund.\u00a0<\/p>

Hadley, renowned for his contributions to R, serves as chief scientist at Posit, PBC, and is an adjunct professor at the University of Auckland, Stanford, and Rice University.\u00a0<\/p>

Garrett, a Ph.D. holder in statistics from Rice University, serves as the director and developer relations at Posit, PBC.<\/p>

About:<\/b> This is a beginner-friendly guide suitable for people who have no previous programming experience. It teaches you R, RStudio, the tidyverse (a set of helpful packages), and the entire data science process. You will learn data cleaning, exploration, modeling, and how to present your results effectively. The book has a lot of exercises that will help you apply your knowledge to solve problems.<\/p>

Get the book: <\/b>R for Data Science<\/a><\/p>

\u00a0<\/p>

7. Introduction to Machine Learning with Python: A Guide for Data Scientists<\/b><\/h3>

Authors:<\/b> Andreas C. M\u00fcller and Sarah Guido wrote this data science book. Andreas M\u00fcller, PhD holder in machine learning from the University of Bonn, works at the Center for Data Science at the New York University. Sarah, a data scientist residing in New York City, worked in many startups.\u00a0<\/p>

About:<\/b> This book is a practical guide to building machine-learning applications using Python. The book focuses less on the maths and more on the practical side of using ML algorithms, making it a beginner-friendly book. Apart from the Scikit-learn library, you will also get familiar with NumPy and Matplotlib libraries.<\/p>

Get the book: <\/b>Introduction to Machine Learning with Python<\/a><\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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8. Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are<\/b><\/h3>

Author:<\/b> Seth Stephens-Davidowitz is a data scientist, economist, and author. Formerly a Google data scientist and a visiting lecturer at the Wharton School of the University of Pennsylvania.<\/p>

About: <\/b>This is one of the best books for data scientists who want to understand the application of data science. \u201c<\/b>Everybody Lies\u201d explores how big data can help us uncover hidden patterns about how people think and behave. The book teaches you to analyze large datasets to answer interesting questions about the world, covering topics like prejudice, decision-making, and even the impact of movies on crime. Aspiring data scientists<\/a> will learn to think critically about data and see how it can be used to challenge common beliefs.<\/p>

Get the book: <\/b>Everybody Lies<\/a><\/p>

\u00a0<\/h2>

Master Data Science with Ivy Pro School<\/b><\/h2>

Data science books are good for sharpening skills. But if you want to build a strong foundation and gain real-world experience, Ivy\u2019s Data Science and AI certification course can help you.<\/p>

This online course is made in partnership with E&ICT Academy IIT Guwahati, so you will be coached by IIT professors and will get an IIT-branded certificate upon completion of the course.<\/p>

This online course will teach you in-demand skills like data analytics, ML, Gen AI, deep learning, etc., with tools like Adv Excel, SQL, Python, Power BI, VBA, Tensorflow, etc.\u00a0<\/p>

With 50+ real-life projects, live doubt-clearing sessions, and placement assistance for holistic growth, the course makes you job-ready in 45 weeks. Visit this page to learn more about Ivy\u2019s Data Science and AI course<\/a>.<\/p>\t\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"

Mastering data science requires constant learning. Books can help you learn new things, improve your techniques, and change how you approach problems. No matter whether you are an aspiring data scientist or a professional, reading data science books lets you effectively transform raw data into powerful insights and tell better stories.\u00a0 To help you on this journey, in this post, we have shared some of the best data science books you must read. So, get ready to become smarter and more skilled.\u00a0 \u00a0 8 Data Science Books that Will Make You Smarter Here are some of the best books for data scientists that will help you sharpen your skills. They will improve your problem-solving ability and help you use data to make sense of this confusing world: 1. Data Science from Scratch: First Principles with Python Author: Joel Grus is a research engineer at the Allen Institute for Artificial Intelligence. Formerly a software engineer at Google and a data scientist at numerous startups. About: This is one of the best data science books for beginners that goes beyond using basic tools. The book covers data manipulation, machine learning models, and even advanced topics like recommendation systems and natural language processing. […]<\/p>\n","protected":false},"author":1001952,"featured_media":12050,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[881],"tags":[],"class_list":["post-12049","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-data-science"],"yoast_head":"\n8 Best Data Science Books You Must Read<\/title>\n<meta name=\"description\" content=\"Best data science books- 1. Data Science from Scratch 2. Data Science for Business 3. Python for Data Analysis 4. Practical Statistics for Data Scientists 5. Storytelling with Data 6. R for Data Science 7. Introduction to Machine Learning with Python 8. 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