This book contains many ready-to-use, focused recipes for high-performance scientific computing and data analysis, from the latest IPython/Jupyter features to the most advanced tricks, to help you write better and faster code. You will apply these state-of-the-art methods to various real-world examples, illustrating topics in applied mathematics, scientific modeling, and machine learning.
It is for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
| Pages : | 548 pages |
| Size : | HTML |
| Downloads: | 61 |
| Created: | 2020-08-29 |
| License: | CC BY-NC-ND 3.0 US |
| Author(s): | Cyrille Rossant |
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