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IPython Interactive Computing and Visualization Cookbook

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子标题:Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science with Python

IPython Interactive Computing and Visualization Cookbook
作者:
Cyrille Rossant
ISBN-10:
1783284811
出版年份:
2014
页数:
423
语言:
English
文件大小:
8.56 MB
文件格式:
PDF

图书描述

The complexity of modern data – in particular Big Data – and the demand to understand it in powerful and productive ways can make effective scientific computing one of the biggest challenges within data science and analysis. IPython is a truly indispensable solution that can help data scientists write intricate code and develop incredibly sophisticated programs and algorithms much more easily. This collection of more than 100 recipes shows you how IPython can help you extend the power of Python – and other languages – for interactive computing.

Beginning with strategies and techniques to help you master the art of High Performance computing with IPython, including recipes on code optimization and dynamic compilation, this data science book then tackles complex data analysis challenges. With an exploration of Bayesian and Frequentist statistics and machine learning, you will find out how IPython can help you manipulate and manage data for maximum insight. You will also find information on signal and image processing and dynamical systems, as the book aims to help you both further and consolidate your knowledge and skills with the dynamism of IPython.

This reliable and comprehensive IPython cookbook provides you with a wide range of data science tutorials and recipes that will transform your approach to data analysis and make the challenges of Python programming easier to overcome.

Find out how to improve your Code to write high-quality, readable, and well-tested programs with IPython
Master all of the new features of the IPython Notebook, including interactive HTML/JavaScript widgets
Analyze data effectively using Bayesian and Frequentist data models with Pandas, PyMC, and R
Learn tips and tricks for successful Python machine learning with Scikit-learn
Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV
Write impressive and fast Python programs with NumPy, PyTables and many more of Python’s range of packages and tools

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