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Learning IPython for Interactive Computing and Data Visualization. Get started with Python for data analysis and numerical computing in the Jupyter not

(ebook) (audiobook) (audiobook) Książka w języku 1
Learning IPython for Interactive Computing and Data Visualization. Get started with Python for data analysis and numerical computing in the Jupyter not Cyrille Rossant - okladka książki

Learning IPython for Interactive Computing and Data Visualization. Get started with Python for data analysis and numerical computing in the Jupyter not Cyrille Rossant - okladka książki

Learning IPython for Interactive Computing and Data Visualization. Get started with Python for data analysis and numerical computing in the Jupyter not Cyrille Rossant - audiobook MP3

Learning IPython for Interactive Computing and Data Visualization. Get started with Python for data analysis and numerical computing in the Jupyter not Cyrille Rossant - audiobook CD

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Python is a user-friendly and powerful programming language. IPython offers a convenient interface to the language and its analysis libraries, while the Jupyter Notebook is a rich environment well-adapted to data science and visualization. Together, these open source tools are widely used by beginners and experts around the world, and in a huge variety of fields and endeavors.

This book is a beginner-friendly guide to the Python data analysis platform. After an introduction to the Python language, IPython, and the Jupyter Notebook, you will learn how to analyze and visualize data on real-world examples, how to create graphical user interfaces for image processing in the Notebook, and how to perform fast numerical computations for scientific simulations with NumPy, Numba, Cython, and ipyparallel. By the end of this book, you will be able to perform in-depth analyses of all sorts of data.

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O autorze książki

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 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.

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