Data Science from Scratch
First Principles with Python
by Joel Grus
Recommended by Balaji S. Srinivasan and Thorsten Heller
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Should I read this?
Recommended by 2 sources and appears in Data Science, Statistics, and Programming.
To really learn data science, you should not only master the toolsdata science libraries, frameworks, modules, and toolkitsbut also understand the ideas and principles underlying them. Updated for Python 3.6, this second edition of Data Science from Scratch shows you how these tools and algorithms work by implementing them from scratch.If you h...
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Why recommended
Recommended by 2 sources and appears in Data Science, Statistics, and Programming.
Recommended by notable people
People and public figures who have recommended this book.
Recommendation Signals
Recommendation proof is sourced from public posts, interviews, reading lists, and cited references.
Balaji S. Srinivasan
“The Best #book to Start your #DataScience Journey Towards #DataScience by @benthecoder1”
Appears In
Not sure if this is the right fit?
Consider First Course in Probability, A by Sheldon Ross.
“Sheldon Ross’s First Course in Probability reads like a clear, calculus-based undergraduate textbook: definitions, step-by-step derivations, and many worked examples aimed at building formal comfort with probability. What works best is its mathematical clarity — it pushes you through proofs and algebra so you understand why common distributions and counting arguments work. The main limitation is tone and pacing: chapters can feel terse and formula-heavy, and the bundled diskette/tooling feels dated for readers expecting modern software support.”
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Each recommendation is collected from a public source — interviews, articles, or curated lists — and linked to its original URL. Books with many verifiable recommendations from respected people rank higher.
Data Science from Scratch
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