BIBLIO is the largest independent book marketplace in the world, with over 100 million books.

Skip to content

Data Science from Scratch: First Principles with Python

Data Science from Scratch: First Principles with Python

Data Science from Scratch: First Principles with Python
Stock photo: cover may vary

Data Science from Scratch: First Principles with Python Paperback - 2019

by Grus, Joel

Add to wish list
  • Used
  • Good
  • Paperback
Used - Good

Description

O'Reilly Media. paperback. Good. 9.5X6.5X1.5. Buy with confidence. Excellent Customer Service & Return policy.
Ask the seller a question Add to wish list
A$34.87
Free Delivery to USA
Standard delivery: 7 to 10 days
More delivery options
Dropship order
Ships from Ausvora INC (Connecticut, United States)
The BIBLIO Guarantee

Details

  • Title Data Science from Scratch: First Principles with Python
  • Author Grus, Joel
  • Binding Paperback
  • Condition Used - Good
  • Pages 403
  • Volumes 1
  • Language ENG
  • Publisher O'Reilly Media
  • Publication date 2019-06-11
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # ANAIS-1492041130
  • ISBN 9781492041139 / 1492041130
  • Weight 1.4 lbs (0.64 kg)
  • Dimensions 9.1 x 6.9 x 0.9 in (23.11 x 17.53 x 2.29 cm)
  • Size 9.5X6.5X1.5
  • Category Computers - General Information
  • Library of Congress subjects Database management, Data mining
  • Library of Congress Catalogue Number 2019304439
  • Dewey Decimal Code 005.756
  • Quantity available 1

About Ausvora INC Connecticut, United States

Biblio member since 2025

We are a U.S.-based online bookstore specializing in quality used books at affordable prices. With over 1 million books in stock, we serve readers, resellers, libraries, and institutions across the United States and internationally.

Terms of Sale:

Fast & Reliable Shipping All orders ship within 1–2 business days. Domestic shipping across the U.S. via USPS or UPS. International shipping available to most countries. 🔁 30-Day Hassle-Free Returns If the book isn't as described, we'll make it right. Enjoy a full 30-day return window with no questions asked.

Browse books from Ausvora INC

Reader reviews for Data Science from Scratch: First Principles with Python

Write a review for this book

There are no reviews for this book yet. Be the first to write a review!

Your review will be anonymous unless you login or create an account first.

Overall rating
Remember: You’re rating the book as a work, not the seller or the condition of the specific copy you purchased!

Important Terms and Guidelines

  • Please focus on the book’s content and context. Also, add any personal comments as to how you enjoyed the book. Substantiate your likes and dislikes. You may make comparisons to other books.
  • Reviews must be at least 140 characters in length.
  • Please do not reveal critical plot elements.
  • This is not a help line. Contact customer support if you need help.
Your review must not include:
  • Obscenities, discriminatory language, or other insulting language not suitable for public domain
  • Advertisements, “spam” content, or references to other products, offers or websites.
  • Email addresses, URLs, phone numbers, physical addresses or other contact information.
  • Overly critical comments about other reviews or reviewers
  • Time-sensitive material (i.e. promotional tours, seminars, lectures, etc.)
  • Availability, price, or alternative ordering/shipping information

From the publisher

To really learn data science, you should not only master the tools--data science libraries, frameworks, modules, and toolkits--but 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 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 the hacking skills you need to get started as a data scientist. Packed with new material on deep learning, statistics, and natural language processing, this updated book shows you how to find the gems in today's messy glut of data.

  • Get a crash course in Python
  • Learn the basics of linear algebra, statistics, and probability--and 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, Nave Bayes, linear and logistic regression, decision trees, neural networks, and clustering
  • Explore recommender systems, natural language processing, network analysis, MapReduce, and databases

About the author

Joel Grus is a research engineer at the Allen Institute for Artificial Intelligence. Previously he worked as a software engineer at Google and a data scientist at several startups. He lives in Seattle, where he regularly attends data science happy hours. He blogs infrequently at joelgrus.com and tweets all day long at @joelgrus.

Please wait a moment while we load the requested page.

tracking-