Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Mastering Numerical Computing with NumPy

You're reading from   Mastering Numerical Computing with NumPy Master scientific computing and perform complex operations with ease

Arrow left icon
Product type Paperback
Published in Jun 2018
Publisher Packt
ISBN-13 9781788993357
Length 248 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Authors (3):
Arrow left icon
Tiago Antao Tiago Antao
Author Profile Icon Tiago Antao
Tiago Antao
Mert Cuhadaroglu Mert Cuhadaroglu
Author Profile Icon Mert Cuhadaroglu
Mert Cuhadaroglu
Umit Mert Cakmak Umit Mert Cakmak
Author Profile Icon Umit Mert Cakmak
Umit Mert Cakmak
Arrow right icon
View More author details
Toc

Table of Contents (11) Chapters Close

Preface 1. Working with NumPy Arrays FREE CHAPTER 2. Linear Algebra with NumPy 3. Exploratory Data Analysis of Boston Housing Data with NumPy Statistics 4. Predicting Housing Prices Using Linear Regression 5. Clustering Clients of a Wholesale Distributor Using NumPy 6. NumPy, SciPy, Pandas, and Scikit-Learn 7. Advanced Numpy 8. Overview of High-Performance Numerical Computing Libraries 9. Performance Benchmarks 10. Other Books You May Enjoy

BLAS and LAPACK

BLAS stands for Basic Linear Algebra Subprograms, and is a standard for dealing with low-level routines for linear algebra operations. Low-level routines include operations such as vector and matrix addition/multiplication, linear combinations, and so on. BLAS provides three different levels for linear algebra operations:

  • BLAS1: Scalar–vector and vector–vector operations
  • BLAS2: Matrix–vector operations
  • BLAS3: Matrix–matrix operations

LAPACK stands for Linear Algebra Package, and contains higher-level operations. LAPACK provides routines for matrix factorizations—such as LU, Cholesky, and QR—and for solving eigenvalue problems. LAPACK mostly depends on BLAS routines.

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image