Picture 1 of 9
Gallery
Picture 1 of 9
Have one to sell?
Practical Linear Algebra for Data Science: From Core Concepts to Applications
US $24.95
ApproximatelyS$ 32.27
or Best Offer
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.
Oops! Looks like we're having trouble connecting to our server.
Refresh your browser window to try again.
Shipping:
US $5.88 (approx S$ 7.60) USPS Media MailTM.
Located in: Las Vegas, Nevada, United States
Delivery:
Estimated between Fri, 10 Oct and Tue, 14 Oct to 94104
Returns:
No returns accepted.
Coverage:
Read item description or contact seller for details. See all detailsSee all details on coverage
(Not eligible for eBay purchase protection programmes)
Seller assumes all responsibility for this listing.
eBay item number:157224988872
Item specifics
- Condition
- Brand
- Unbranded
- Book Title
- Practical Linear Algebra for Data Science: From Core Concepts to
- MPN
- Does not apply
- ISBN
- 9781098120610
About this product
Product Identifiers
Publisher
O'reilly Media, Incorporated
ISBN-10
1098120612
ISBN-13
9781098120610
eBay Product ID (ePID)
16057246179
Product Key Features
Number of Pages
300 Pages
Language
English
Publication Name
Practical Linear Algebra for Data Science : from Core concepts to Applications Using Python
Subject
Algebra / Linear, Data Processing
Publication Year
2022
Type
Textbook
Subject Area
Mathematics, Computers
Format
Trade Paperback
Dimensions
Item Height
0.9 in
Item Weight
19.9 Oz
Item Length
9.1 in
Item Width
7 in
Additional Product Features
Intended Audience
Trade
LCCN
2022-301984
Illustrated
Yes
Synopsis
If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way it's presented in decades-old textbooks is much different from how professionals use linear algebra today to solve real-world modern applications. This practical guide from Mike X Cohen teaches the core concepts of linear algebra as implemented in Python, including how they're used in data science, machine learning, deep learning, computational simulations, and biomedical data processing applications. Armed with knowledge from this book, you'll be able to understand, implement, and adapt myriad modern analysis methods and algorithms. Ideal for practitioners and students using computer technology and algorithms, this book introduces you to: The interpretations and applications of vectors and matrices Matrix arithmetic (various multiplications and transformations) Independence, rank, and inverses Important decompositions used in applied linear algebra (including LU and QR) Eigendecomposition and singular value decomposition Applications including least-squares model fitting and principal components analysis
LC Classification Number
QA185.D37C64 2022
Item description from the seller
Seller feedback (2,116)
This item (1)
All items (2,116)
- eBay automated feedback- Feedback left by buyer.Past monthOrder delivered on time with no issues
- eBay automated feedback- Feedback left by buyer.Past monthOrder delivered on time with no issues
- eBay automated feedback- Feedback left by buyer.Past monthOrder delivered on time with no issues
- n***a (2261)- Feedback left by buyer.Past monthVerified purchase👍🏾