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IPython Interactive Computing and Visualization Cookbook
IPython Interactive Computing and Visualization Cookbook

IPython Interactive Computing and Visualization Cookbook: Sharpen your high-performance numerical computing and data science skills with Jupyter Notebook

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Profile Icon Fawaz Sammani
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Course Jun 2019 547 pages 1st Edition
Arrow left icon
Profile Icon Fawaz Sammani
Arrow right icon
Course Jun 2019 547 pages 1st Edition

Key benefits

  • Use Jupyter Notebook for interactive data science and visualization
  • Get up to speed with high-performance computing and scientific modeling
  • Learn best practices and tricks to write high-quality, readable, and well-tested programs

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 they constitute an ideal gateway to the platform. This course is equipped with several ready-to-use, focused recipes for high-performance scientific computing and data analysis to help you write better and faster code. You’ll be able to apply your learnings to various real-world examples, ranging from applied mathematics, scientific modeling, to machine learning. The course introduces you to effective programming techniques such as code quality and reproducibility, code optimization, and graphics card programming. You’ll also learn how to use different features of IPython and Jupyter Notebook in data science, signal and image processing, and applied mathematics. By the end of this course, you’ll learn how to easily analyze and visualize all types of data in Jupyter Notebook.

Who is this book for?

This course is ideal for students, researchers, teachers, engineers, analysts, and hobbyists who are interested in numerical computing and data science. 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

  • Visualize data and create interactive plots in the Jupyter Notebook
  • Write fast Python programs with NumPy, ctypes, Numba, and other libraries
  • Analyze data with Bayesian or frequentist statistics
  • Simulate deterministic and stochastic dynamical systems in Python
  • Get familiar with math in Python using SymPy and Sage
  • Profile and optimize your code and conduct reproducible interactive computing experiments

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jun 28, 2019
Length: 547 pages
Edition : 1st
Language : English
ISBN-13 : 9781838823603
Category :
Languages :
Concepts :
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Product Details

Publication date : Jun 28, 2019
Length: 547 pages
Edition : 1st
Language : English
ISBN-13 : 9781838823603
Category :
Languages :
Concepts :
Tools :

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Table of Contents

11 Chapters
A Tour of Interactive Computing with Jupyter and IPython Chevron down icon Chevron up icon
Data Visualization Chevron down icon Chevron up icon
Statistical Data Analysis Chevron down icon Chevron up icon
Machine Learning Chevron down icon Chevron up icon
Numerical Optimization Chevron down icon Chevron up icon
Signal Processing Chevron down icon Chevron up icon
Image and Audio Processing Chevron down icon Chevron up icon
Deterministic Dynamical Systems Chevron down icon Chevron up icon
Stochastic Dynamical Systems Chevron down icon Chevron up icon
Graphs, Geometry, and Geographic Information Systems Chevron down icon Chevron up icon
Symbolic and Numerical Mathematics Chevron down icon Chevron up icon
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