Numerical Python
33%
off

Numerical Python : Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib

3.66 (3 ratings by Goodreads)
By (author) 

Free delivery worldwide

Available. Dispatched from the UK in 4 business days
When will my order arrive?

Description

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more.

Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis.

After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning.

What You'll Learn



Work with vectors and matrices using NumPy

Plot and visualize data with Matplotlib

Perform data analysis tasks with Pandas and SciPy

Review statistical modeling and machine learning with statsmodels and scikit-learn

Optimize Python code using Numba and Cython


Who This Book Is For

Developers who want to understand how to use Python and its related ecosystem for numerical computing.
show more

Product details

  • Paperback | 700 pages
  • 178 x 254 x 36.83mm | 1,355g
  • Berkley, United States
  • English
  • Revised
  • 2nd ed.
  • 63 Illustrations, color; 105 Illustrations, black and white; XXIII, 700 p. 168 illus., 63 illus. in color.
  • 1484242459
  • 9781484242452
  • 561,875

Back cover copy

Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more.

Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis.

After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning.
show more

Table of contents

Numerical Python
1. Introduction to Computing with Python
2. Vectors, Matrices and Multidimensional Arrays
3. Symbolic Computing
4. Plotting and Visualization
5. Equation Solving
6. Optimization
7. Interpolation
8. Integration
9. Ordinary Differential Equations
10. Sparse Matrices and Graphs
11. Partial Differential Equations
12. Data Processing and Analysis
13. Statistics
14. Statistical Modeling
15. Machine Learning
16. Bayesian Statistics
17. Signal and Image Processing
18. Data Input and Output
19. Code Optimization
show more

About Robert Johansson

Robert Johansson is a numerical Python expert and computational scientist who has worked with SciPy, NumPy and QuTiP, an open-source Python framework for simulating the dynamics of quantum systems.
show more

Rating details

3 ratings
3.66 out of 5 stars
5 0% (0)
4 67% (2)
3 33% (1)
2 0% (0)
1 0% (0)
Book ratings by Goodreads
Goodreads is the world's largest site for readers with over 50 million reviews. We're featuring millions of their reader ratings on our book pages to help you find your new favourite book. Close X