The Resource IPython interactive computing and visualization cookbook : over 100 handson recipes to sharpen your skills in highperformance numerical computing and data science in the Jupyter Notebook, Cyrille Rossant
IPython interactive computing and visualization cookbook : over 100 handson recipes to sharpen your skills in highperformance numerical computing and data science in the Jupyter Notebook, Cyrille Rossant
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The item IPython interactive computing and visualization cookbook : over 100 handson recipes to sharpen your skills in highperformance numerical computing and data science in the Jupyter Notebook, Cyrille Rossant represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.This item is available to borrow from 2 library branches.
Resource Information
The item IPython interactive computing and visualization cookbook : over 100 handson recipes to sharpen your skills in highperformance numerical computing and data science in the Jupyter Notebook, Cyrille Rossant represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.
This item is available to borrow from 2 library branches.
 Summary
 "Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. Key Features Leverage the Jupyter Notebook for interactive data science and visualization Become an expert in highperformance computing and visualization for data analysis and scientific modeling A comprehensive coverage of scientific computing through many handson, exampledriven recipes with detailed, stepbystep explanationsBook DescriptionPython 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 readytouse, focused recipes for highperformance 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 stateoftheart methods to various realworld 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, highperformance computing through justintime 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 Master all features of the Jupyter Notebook Code better: write highquality, readable, and welltested programs; profile and optimize your code; and conduct reproducible interactive computing experiments Visualize data and create interactive plots in the Jupyter Notebook Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikitlearn) Gain valuable insights into signals, images, and sounds with SciPy, scikitimage, and OpenCV Simulate deterministic and stochastic dynamical systems in Python Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theoryWho this book is forThis book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods."EBSCO
 Language
 eng
 Edition
 Second edition.
 Extent
 1 online resource (1 volume)
 Note
 Includes index
 Contents

 Chapter 1: A Tour of Interactive Computing with Jupyter and IPython
 Chapter 2: Best Practices in Interactive Computing
 Chapter 3: Mastering the Jupyter Notebook
 Chapter 4: Profiling and Optimization
 Chapter 5: HighPerformance Computing
 Chapter 6: Data Visualization
 Chapter 7: Statistical Data Analysis
 Chapter 8: Machine Learning
 Chapter 9: Numerical Optimization
 Chapter 10: Signal Processing
 Chapter 11: Image and Audio Processing
 Chapter 12: Deterministic Dynamical Systems
 Chapter 13: Stochastic Dynamical Systems
 Chapter 14: Graphs, Geometry, and Geographic Information Systems
 Chapter 15: Symbolic and Numerical Mathematics
 Isbn
 9781785888632
 Label
 IPython interactive computing and visualization cookbook : over 100 handson recipes to sharpen your skills in highperformance numerical computing and data science in the Jupyter Notebook
 Title
 IPython interactive computing and visualization cookbook
 Title remainder
 over 100 handson recipes to sharpen your skills in highperformance numerical computing and data science in the Jupyter Notebook
 Statement of responsibility
 Cyrille Rossant
 Language
 eng
 Summary
 "Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. Key Features Leverage the Jupyter Notebook for interactive data science and visualization Become an expert in highperformance computing and visualization for data analysis and scientific modeling A comprehensive coverage of scientific computing through many handson, exampledriven recipes with detailed, stepbystep explanationsBook DescriptionPython 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 readytouse, focused recipes for highperformance 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 stateoftheart methods to various realworld 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, highperformance computing through justintime 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 Master all features of the Jupyter Notebook Code better: write highquality, readable, and welltested programs; profile and optimize your code; and conduct reproducible interactive computing experiments Visualize data and create interactive plots in the Jupyter Notebook Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikitlearn) Gain valuable insights into signals, images, and sounds with SciPy, scikitimage, and OpenCV Simulate deterministic and stochastic dynamical systems in Python Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theoryWho this book is forThis book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods."EBSCO
 Cataloging source
 UMI
 http://library.link/vocab/creatorName
 Rossant, Cyrille
 Dewey number
 005.13/3
 Illustrations
 illustrations
 Index
 index present
 LC call number
 QA76.73.P98
 Literary form
 non fiction
 Nature of contents
 dictionaries
 http://library.link/vocab/subjectName

 Python (Computer program language)
 Command languages (Computer science)
 Information visualization
 Interactive computer systems
 Command languages (Computer science)
 Information visualization
 Interactive computer systems
 Python (Computer program language)
 Label
 IPython interactive computing and visualization cookbook : over 100 handson recipes to sharpen your skills in highperformance numerical computing and data science in the Jupyter Notebook, Cyrille Rossant
 Note
 Includes index
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 Chapter 1: A Tour of Interactive Computing with Jupyter and IPython  Chapter 2: Best Practices in Interactive Computing  Chapter 3: Mastering the Jupyter Notebook  Chapter 4: Profiling and Optimization  Chapter 5: HighPerformance Computing  Chapter 6: Data Visualization  Chapter 7: Statistical Data Analysis  Chapter 8: Machine Learning  Chapter 9: Numerical Optimization  Chapter 10: Signal Processing  Chapter 11: Image and Audio Processing  Chapter 12: Deterministic Dynamical Systems  Chapter 13: Stochastic Dynamical Systems  Chapter 14: Graphs, Geometry, and Geographic Information Systems  Chapter 15: Symbolic and Numerical Mathematics
 Control code
 1024148073
 Dimensions
 unknown
 Edition
 Second edition.
 Extent
 1 online resource (1 volume)
 Form of item
 online
 Isbn
 9781785888632
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other physical details
 illustrations
 http://library.link/vocab/ext/overdrive/overdriveId

 cl0500000942
 9532bf51477049a887ab7e22142b609b
 Sound
 unknown sound
 Specific material designation
 remote
 System control number
 (OCoLC)1024148073
 Label
 IPython interactive computing and visualization cookbook : over 100 handson recipes to sharpen your skills in highperformance numerical computing and data science in the Jupyter Notebook, Cyrille Rossant
 Note
 Includes index
 Carrier category
 online resource
 Carrier category code

 cr
 Carrier MARC source
 rdacarrier
 Content category
 text
 Content type code

 txt
 Content type MARC source
 rdacontent
 Contents
 Chapter 1: A Tour of Interactive Computing with Jupyter and IPython  Chapter 2: Best Practices in Interactive Computing  Chapter 3: Mastering the Jupyter Notebook  Chapter 4: Profiling and Optimization  Chapter 5: HighPerformance Computing  Chapter 6: Data Visualization  Chapter 7: Statistical Data Analysis  Chapter 8: Machine Learning  Chapter 9: Numerical Optimization  Chapter 10: Signal Processing  Chapter 11: Image and Audio Processing  Chapter 12: Deterministic Dynamical Systems  Chapter 13: Stochastic Dynamical Systems  Chapter 14: Graphs, Geometry, and Geographic Information Systems  Chapter 15: Symbolic and Numerical Mathematics
 Control code
 1024148073
 Dimensions
 unknown
 Edition
 Second edition.
 Extent
 1 online resource (1 volume)
 Form of item
 online
 Isbn
 9781785888632
 Media category
 computer
 Media MARC source
 rdamedia
 Media type code

 c
 Other physical details
 illustrations
 http://library.link/vocab/ext/overdrive/overdriveId

 cl0500000942
 9532bf51477049a887ab7e22142b609b
 Sound
 unknown sound
 Specific material designation
 remote
 System control number
 (OCoLC)1024148073
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