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IPython Interactive Computing and Visualization Cookbook. Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook - Second Edition

Język publikacji: angielskim
IPython Interactive Computing and Visualization Cookbook. Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook - Second Edition Cyrille Rossant - okladka książki

IPython Interactive Computing and Visualization Cookbook. Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science in the Jupyter Notebook - Second Edition Cyrille Rossant - okladka książki

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Python is one of the leading open source platforms for data science and numerical computing. IPython and the associated Jupyter Notebook offer efficient interfaces to Python for data analysis and interactive visualization, and they constitute an ideal gateway to the platform.

IPython Interactive Computing and Visualization Cookbook, Second Edition 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.

The first part of the book covers programming techniques: code quality and reproducibility, code optimization, high-performance computing through just-in-time compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.

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O autorze książki

Cyrille Rossant, PhD, is a neuroscience researcher and software engineer at University College London. He is a graduate of École Normale Supérieure, Paris, where he studied mathematics and computer science. He has also worked at Princeton University and Collège de France. While working on data science and software engineering projects, he gained experience in numerical computing, parallel computing, and high-performance data visualization. He is the author of Learning IPython for Interactive Computing and Data Visualization, Second Edition, Packt Publishing.

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