Data Science from Scratch, Python, Machine Learning Grus O'Reilly PBK 2019

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ApproximatelyRM 138.38
Condition:
Very Good
“O'Reilly Media, 2019 (Second Edition). Clean, unmarked interior. Softcover, clean & bright, light ”... Read moreabout condition
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eBay item number:116499822924
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Item specifics

Condition
Very Good
A book that has been read but is in excellent condition. No obvious damage to the cover, with the dust jacket included for hard covers. No missing or damaged pages, no creases or tears, and no underlining/highlighting of text or writing in the margins. May be very minimal identifying marks on the inside cover. Very minimal wear and tear. See all condition definitionsopens in a new window or tab
Seller Notes
“O'Reilly Media, 2019 (Second Edition). Clean, unmarked interior. Softcover, clean & bright, light ...
Country of Origin
United States
Signed
No
Literary Movement
Modern Non-Fiction, Educational Technology, Data Science and Mach
Narrative Type
Nonfiction
Inscribed
No
Personalized
No
Intended Audience
Adults
Genre
Computer Science, Data Science, Programming, Educational, Non-Fic
Ex Libris
No
Signed By
NA
Features
illustrated, paperback, 2nd edition
Book Series
Data Science From Scratch
Original Language
English
Era
21st Century, 2010s, Contemporary
Book Title
Data Science from Scratch: First Principles with Python
Vintage
No
Personalize
No
Topic
Data Science, Python, Machine Learning, Deep Learning, Statistics
Edition
Second Edition
ISBN
9781492041139
Category

About this product

Product Identifiers

Publisher
O'reilly Media, Incorporated
ISBN-10
1492041130
ISBN-13
9781492041139
eBay Product ID (ePID)
5038681800

Product Key Features

Number of Pages
403 Pages
Language
English
Publication Name
Data Science from Scratch : First Principles with Python
Publication Year
2019
Subject
Data Modeling & Design, Databases / Data Mining, Statistics, Programming Languages / Python, Business Mathematics
Type
Textbook
Subject Area
Computers, Business & Economics
Author
Joel Grus
Format
Trade Paperback

Dimensions

Item Height
1 in
Item Weight
24.5 Oz
Item Length
9.1 in
Item Width
7 in

Additional Product Features

Edition Number
2
Intended Audience
Scholarly & Professional
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.312
Synopsis
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, Naïve Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases, 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, Na ve Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
LC Classification Number
QA76.9.D343

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    Ordering the true 1st edition of this book proved to be an ordeal. It took me four goes to finally land one! It seems for this specific book the automated form filling software used by many sellers puts forward the multiple reprints between 1999 and 2001 as 1st editions. Thankfully this seller provided detailed photos, so I could order in confidence. The book arrived on the 1st day of the delivery window and was very securely boxed up. A happy customer.
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