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Choosing the “best” books for learning data science can depend on your background, learning preferences, and specific areas of interest within data science. Here are ten highly regarded books that cover various aspects of data science. Please note that the order does not indicate a ranking, as different books may cater to different needs.
1. “The Data Science Handbook” by Field Cady
- Summary: This book offers insights into the careers and techniques of various successful data scientists. It includes interviews with professionals from companies like Facebook, LinkedIn, and Google, providing practical advice and real-world experiences.
- Comparison: It stands out for its unique approach of showcasing the diverse journeys and perspectives of data scientists.
2. “Python for Data Analysis” by Wes McKinney
- Summary: Focused on practical data analysis using Python, this book covers essential libraries like NumPy, pandas, and Matplotlib. It’s particularly useful for those interested in data manipulation and exploration.
- Comparison: Known for its hands-on approach and clear explanations, it’s a great choice for beginners and those looking to strengthen their Python data analysis…
