Numerical Python
Scientific Computing and Data Science Applications with Numpy, SciPy and Matplotlib
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1.0 • 1 Rating
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- $59.99
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- $59.99
Publisher 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.
Customer Reviews
No page numbers in the index
This book doesn’t have the page numbers listed next to the items in the index section. I use the index of books often to look up specifice material. When someone purchases a book like this, and there is an index, it’s expected to have the page numbers included. I’ll change my rating after you fix the issue.