Data Science from Scratch
First Principles with Python
Publisher: O'Reilly Media
Final Release Date: April 2015
Pages: 330

Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch.

If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out.

  • Get a crash course in Python
  • Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science
  • Collect, explore, clean, munge, and manipulate data
  • Dive into the fundamentals of machine learning
  • Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering
  • Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
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oreillyData Science from Scratch
 
4.1

(based on 7 reviews)

Ratings Distribution

  • 5 Stars

     

    (4)

  • 4 Stars

     

    (2)

  • 3 Stars

     

    (0)

  • 2 Stars

     

    (0)

  • 1 Stars

     

    (1)

86%

of respondents would recommend this to a friend.

Pros

  • Easy to understand (6)
  • Helpful examples (4)
  • Concise (3)
  • Well-written (3)

Cons

No Cons

Best Uses

  • Novice (5)
  • Intermediate (4)
  • Student (3)
    • Reviewer Profile:
    • Developer (3)

Reviewed by 7 customers

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(4 of 8 customers found this review helpful)

 
1.0

could be better

By andrea

from osnabrueck, germany

Comments about oreilly Data Science from Scratch:

The idea of the book is nice, I still think is a useful book, but:
1. you'll not learn math behind this or the methods will be explained (it's good for a programming, though)
2. regarding programming part, I think that people would benefit more if there were some actual exercises for them to do, not just "type in this code" attitude
3. would be nice if all of the data sets are actually generated in a book, not just "there is some data set with 2000 points, that I just pulled out of my ass"
4. more usage of numpy would be useful
5. all of the titles which contain "learn from scratch" suck
6. the whole american attitude with "Congratulations! You now work in DataScienster! Welcome aboard!" is annoying and treats people like idiots.
The book is actually not that bad as I described it, but sometimes, while working you'll be so annoyed but all of these details. Good thing that's not expensive.

 
4.0

Good intro to Python

By Fialko

from New Zealand

About Me Scientist

Pros

  • Easy to understand
  • Helpful examples

Cons

  • Not comprehensive enough
  • Too basic

Best Uses

  • Novice

Comments about oreilly Data Science from Scratch:

This book teaches you more Python tricks than data science. If you want to learn and understand (I maintain UNDERSTAND) basics of data science, then "Machine learning" course by Andrew Ng is probably the best start.

 
5.0

Helps Build a Solid Foundation

By Gideon

from Boston

About Me Developer

Verified Reviewer

Pros

  • Easy to understand

Cons

    Best Uses

    • Intermediate
    • Novice
    • Student

    Comments about oreilly Data Science from Scratch:

    Joel Grus's repo that accompany's this book is a phenomenal reference when building intuition behind how a given learning algorithm works.

    (1 of 1 customers found this review helpful)

     
    4.0

    Nice introduction to Data Science

    By said

    from Lebanon

    Verified Buyer

    Pros

    • Concise
    • Easy to understand
    • Well-written

    Cons

      Best Uses

      • Intermediate
      • Novice

      Comments about oreilly Data Science from Scratch:

      Easy reading (from scratch). Good for a quick reference on most used techniques

      (1 of 1 customers found this review helpful)

       
      5.0

      Very good for reviewing concepts and python style

      By Joel

      from Enumclaw, WA

      Verified Buyer

      Pros

      • Concise
      • Easy to understand
      • Helpful examples

      Cons

        Best Uses

        • Intermediate
        • Student

        Comments about oreilly Data Science from Scratch:

        I am working through the book typing in all the code and then running it. It is a great review for all the concepts I have gotten to so far, and also a great improvement for my python style.

        (17 of 19 customers found this review helpful)

         
        5.0

        The book I wish I read between Python & Pandas - Recommended

        By Gnomic

        from Richmond, VA

        About Me Developer, Educator, Maker

        Verified Reviewer

        Pros

        • Accurate
        • Comprehensive
        • Concise
        • Easy to understand
        • Helpful examples
        • Well-written

        Cons

        • Not Latest Python Version

        Best Uses

        • Intermediate
        • Novice
        • Student

        Comments about oreilly Data Science from Scratch:

        I have dozens of books on python, pandas, and data science. Most I find either too basic or too advanced. This book starts with one of the best, most consice python tutorials I've ever read, and builds up to the other tools (matlib, pandas, etc.) in a very easy to understand progression - covering that middle ground as it progresses to more advanced topics. This is the book I wish I'd read before Python for Data Analysis (another great book!) Only negative is that it is written in python 2.7. Get with the program folks - start with the latest version (3.4 at the time of this review). If there is one improvement I'd like to see is that each chapter/topic ends with a 1 page summary cheat sheet.

        (6 of 6 customers found this review helpful)

         
        5.0

        Great to start with Data Science and keep your hands dirty!

        By Dominik Landau

        from Berlin

        About Me Developer

        Verified Buyer

        Pros

        • Easy to understand
        • Helpful examples
        • Well-written

        Cons

          Best Uses

          • Novice

          Comments about oreilly Data Science from Scratch:

          For me it was a great book to dive into the big and complex world of Data Science. I am a professional software developer, but almost never used Python previously. This book introduced me to Python. The quality of code is very good - I enjoyed reading listings.

          Highly recommended as a first intro book into Data Science and ML.

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