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Python. Mastering Numerical Computing with NumPy teaches you how to achieve expert level competency to perform complex operations, with in-depth;
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like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to;
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Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists;
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management * Performing numerical computing using NumPy and SciPy * Concepts and programming for symbolic computing using SymPy * Using the;
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are an experienced Python developer who intends to drive your numerical and scientific applications with NumPy, this book is for you. Prior;
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A step-by-step guide, packed with examples of practical numerical analysis that will give you a comprehensive, but concise overview;
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The book is written in beginner's guide style with each aspect of NumPy demonstrated with real world examples and required screenshots. If;
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performance of numerical computing, such as the Numpy and Scipy modules. The Python source code and data files are available on the author's website;
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performance of numerical computing, such as the Numpy and Scipy modules. The Python source code and data files are available on the author's website;
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SciPy is open-source software for mathematics, science, and engineering. The SciPy library is built to work with NumPy arrays, and provides;
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Numerical Computing with MATLAB is a lively textbook for an introductory course in numerical methods, MATLAB and technical computing.;
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interactive computing experiments Visualize data and create interactive plots in the Jupyter Notebook Write blazingly fast Python programs with NumPy;
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: - die interaktive IPython-Shell als primäre Programmierumgebung - die Features von NumPy (Numerical Python) - die Datenanalyse-Tools der Pandas-Bibliothek;
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of Python in the Jupyter Notebook * Analyze and visualize data with pandas, NumPy, matplotlib, and seaborn * Perform highly-efficient numerical;
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0;...
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in numerical analysis, primarily for new graduate students in engineering and physical science. Along with mastering the fundamentals of numerical;
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in numerical analysis, primarily for new graduate students in engineering and physical science. Along with mastering the fundamentals of numerical;
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numerical and scientific computing using NumPy and SciPy on Spark. * Use Predictive Model Markup Language (PMML) in Spark for statistical data;
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Emphasis on cause and effect in numerical mathematics. Flexibility with computing languages--the book is not specific to any one;
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Tackle the most sophisticated problems associated with scientific computing and data manipulation using SciPy About This Book;
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This highly successful and scholarly book introduces students with diverse backgrounds to the various types of mathematical analysis that;
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all of these and more, with exercises and labs throughout.;
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up and running with Python numerical computations * Explore numerical computing and mathematical libraries using Python 3.x code with SciPy;
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algorithms and scientific computing. It uses a theorem-free approach with just the right balance between mathematics and numerical algorithms. It;
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Offering a clear, precise, and accessible presentation, complete with MATLAB programs, this new Third Edition of Elementary Numerical;
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This is an introductory single-term numerical analysis text with a modern scientific computing flavor. It offers an immediate immersion;
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Taking an interdisciplinary approach, this new book provides a modern introduction to scientific computing, exploring numerical methods;
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