Learn to use IPython and Jupyter Notebook for your data analysis and visualization work
Key Features
Book Description
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 constitute an ideal gateway to the platform.
This second edition of IPython Interactive Computing and Visualization Cookbook 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.
What you will learn
Who This Book Is For
This book 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.
Table of Contents
"synopsis" may belong to another edition of this title.
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 has 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, the prequel of this cookbook.
"About this title" may belong to another edition of this title.
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