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

Skip to content

Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics [Paperback] Nield, Thomas

Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics [Paperback] Nield, Thomas

Essential Math for Data Science: Take Control of Your Data with Fundamental
Stock photo: cover may vary

Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics [Paperback] Nield, Thomas Paperback - 2022

by Thomas Nield

Add to wish list
  • Used
New

Description

Like New. 0x0x0.
Ask the seller a question Add to wish list
A$64.88
A$5.76 Delivery within USA
Standard delivery: 4 to 14 days
More delivery options
Dropship order
Ships from Mediaoutletdeal1 (Virginia, United States)
The BIBLIO Guarantee

Details

  • Title Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics [Paperback] Nield, Thomas
  • Author Thomas Nield
  • Binding Paperback
  • Condition New
  • Pages 349
  • Volumes 1
  • Language ENG
  • Publisher O'Reilly Media
  • Publication date 2022-07-05
  • Illustrated Yes
  • Features Illustrated, Index
  • Bookseller's Inventory # 1098102932_used
  • ISBN 9781098102937 / 1098102932
  • Weight 1.24 lbs (0.56 kg)
  • Dimensions 9.19 x 7 x 0.73 in (23.34 x 17.78 x 1.85 cm)
  • Size 0x0x0
  • Category Computers - General Information
  • Library of Congress subjects Probabilities, Mathematical statistics
  • Dewey Decimal Code 005.701
  • Quantity available 4

About Mediaoutletdeal1 Virginia, United States

Biblio member since 2014

Terms of Sale:

30 day return guarantee, with full refund including original shipping costs for up to 30 days after delivery if an item arrives misdescribed or damaged.

Browse books from Mediaoutletdeal1

Reader reviews for Essential Math for Data Science: Take Control of Your Data with Fundamental Linear Algebra, Probability, and Statistics [Paperback] Nield, Thomas

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

Master the math needed to excel in data science, machine learning, and statistics. In this book author Thomas Nield guides you through areas like calculus, probability, linear algebra, and statistics and how they apply to techniques like linear regression, logistic regression, and neural networks. Along the way you'll also gain practical insights into the state of data science and how to use those insights to maximize your career.

Learn how to:

  • Use Python code and libraries like SymPy, NumPy, and scikit-learn to explore essential mathematical concepts like calculus, linear algebra, statistics, and machine learning
  • Understand techniques like linear regression, logistic regression, and neural networks in plain English, with minimal mathematical notation and jargon
  • Perform descriptive statistics and hypothesis testing on a dataset to interpret p-values and statistical significance
  • Manipulate vectors and matrices and perform matrix decomposition
  • Integrate and build upon incremental knowledge of calculus, probability, statistics, and linear algebra, and apply it to regression models including neural networks
  • Navigate practically through a data science career and avoid common pitfalls, assumptions, and biases while tuning your skill set to stand out in the job market

Please wait a moment while we load the requested page.

tracking-