Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science with Python
About This Book
Who This Book Is For
Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists... Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
What You Will Learn
In Detail
IPython is at the heart of the Python scientific stack. With its widely acclaimed web-based notebook, IPython is today an ideal gateway to data analysis and numerical computing in Python.
IPython Interactive Computing and Visualization Cookbook contains many ready-to-use focused recipes for high-performance scientific computing and data analysis. The first part covers programming techniques, including code quality and reproducibility; code optimization; high-performance computing through dynamic 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.
Cyrille Rossant
Cyrille Rossant is a researcher in neuroinformatics, and is a graduate of Ecole Normale Superieure, Paris, where he studied mathematics and computer science. He has worked at Princeton University, University College London, and College de France. As part of his data science and software engineering projects, he gained experience in machine learning, high-performance computing, parallel computing, and big data visualization. He is one of the developers of Vispy, a high-performance visualization package in Python. He is the author of Learning IPython for Interactive Computing and Data Visualization, Packt Publishing, a beginner-level introduction to data analysis in Python, and the prequel of this book.
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