Ipython interactive computing visualization de rossant cyrille (70 resultados)

Paperback. Condición: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Condición: Good. Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. About This Book ? Leverage the Jupyter Notebook for interactive data science and visualization ? Become an expert in high-performance computing and visualization for data analysis and scientific modeling ? A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Who This Book Is For This 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. What You Will Learn ? Master all features of the Jupyter Notebook ? Code better: write high-quality, readable, and well-tested 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 (scikit-learn) ? Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, 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 theory In Detail 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. IPython Interactive Computing and Visualization Cookbook, Second Edition 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. Style and approach IPython Interactive Computing and Visualization Cookbook, Second Edition is a practical, hands-on book that will teach you how to analyze and visualize all kinds of data in the Jupyter Notebook.…

Condición: Very Good. Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. About This Book ? Leverage the Jupyter Notebook for interactive data science and visualization ? Become an expert in high-performance computing and visualization for data analysis and scientific modeling ? A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Who This Book Is For This 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. What You Will Learn ? Master all features of the Jupyter Notebook ? Code better: write high-quality, readable, and well-tested 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 (scikit-learn) ? Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, 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 theory In Detail 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. IPython Interactive Computing and Visualization Cookbook, Second Edition 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. Style and approach IPython Interactive Computing and Visualization Cookbook, Second Edition is a practical, hands-on book that will teach you how to analyze and visualize all kinds of data in the Jupyter Notebook.…

Condición: Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Paperback. Condición: Fair. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.

Condición: Very Good. Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. About This Book ? Leverage the Jupyter Notebook for interactive data science and visualization ? Become an expert in high-performance computing and visualization for data analysis and scientific modeling ? A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Who This Book Is For This 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. What You Will Learn ? Master all features of the Jupyter Notebook ? Code better: write high-quality, readable, and well-tested 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 (scikit-learn) ? Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, 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 theory In Detail 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. IPython Interactive Computing and Visualization Cookbook, Second Edition 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. Style and approach IPython Interactive Computing and Visualization Cookbook, Second Edition is a practical, hands-on book that will teach you how to analyze and visualize all kinds of data in the Jupyter Notebook.…

Condición: Good. Learn to use IPython and Jupyter Notebook for your data analysis and visualization work. About This Book ? Leverage the Jupyter Notebook for interactive data science and visualization ? Become an expert in high-performance computing and visualization for data analysis and scientific modeling ? A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations Who This Book Is For This 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. What You Will Learn ? Master all features of the Jupyter Notebook ? Code better: write high-quality, readable, and well-tested 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 (scikit-learn) ? Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, 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 theory In Detail 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. IPython Interactive Computing and Visualization Cookbook, Second Edition 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. Style and approach IPython Interactive Computing and Visualization Cookbook, Second Edition is a practical, hands-on book that will teach you how to analyze and visualize all kinds of data in the Jupyter Notebook.…

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Paperback. Condición: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condición: Good. No Jacket. Pages can have notes/highlighting. Spine may show signs of wear. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condición: Very Good. No Jacket. May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

Paperback. Condición: Very Good. The book has been read, but is in excellent condition. Pages are intact and not marred by notes or highlighting. The spine remains undamaged.

Paperback. Condición: Very Good. Learning IPython for Interactive Computing and Data Visualization This book is in very good condition and will be shipped within 24 hours of ordering. The cover may have some limited signs of wear but the pages are clean, intact and the spine remains undamaged. This book has clearly been well maintained and looked after thus far. Money back guarantee if you are not satisfied. See all our books here, order more than 1 book and get discounted shipping. .…

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Paperback. Condición: Very Good. Second Edition. 527 pages; B&W illustrations. Graphs. Very Good condition. No noteworthy defects. No markings.; - Your satisfaction is our priority. We offer free returns and respond promptly to all inquiries. Your item will be packaged with care and ship on the same or next business day. Buy with confidence.…

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