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and scientists who have basic Python knowledge and who are keen to perform scientific and numerical computations with SciPy.;
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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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visualize data with Matplotlib Perform data analysis tasks with Pandas and SciPy Review statistical modeling and machine learning with;
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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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computer scientist with a proficiency in Python and familiarity with IPython, this is the book for you. Some basic knowledge of numerical methods;
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interactive data science and visualization Become an expert in high-performance computing and visualization for data analysis and scientific modeling;
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This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on;
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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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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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complete analysis of methods for scientific computing with careful proofs and scientific background.An in-depth treatment of the topics;
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Is For Scientists and engineers who would like to use Scala for their scientific and numerical computing needs. A basic familiarity with;
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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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Scientific Computing for Scientists and Engineers is designed to teach undergraduate students relevant numerical methods and required;
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field of scientific computing - making it a valuable resource for all students and professionals interested in the history of numerical analysis;
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Vietnam Academy of Science and Technology, the Interdisciplinary Center for Scientific Computing (IWR) of Heidelberg University and the Vietnam;
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on usefulness, longevity, and breadth, Lessons in Scientific Computing will serve as a one stop shop for students taking a unified course;
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on usefulness, longevity, and breadth, Lessons in Scientific Computing will serve as a one stop shop for students taking a unified course;
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This is the revised and expanded second edition of the hugely popular Numerical Recipes: the Art of Scientific Computing. The product of a;
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from elementary to advanced, and all the latest fields in scientific computing are covered such as matrices, numerical analysis, neural;
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from elementary to advanced, and all the latest fields in scientific computing are covered such as matrices, numerical analysis, neural;
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carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on numerical modeling of fluids and;
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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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Scientific Computing in Chemical Engineering gives the state of the art from the point of view of the numerical mathematicians as well as;
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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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Enhance the power of NumPy and start boosting your scientific computing capabilities Key Features Grasp all aspects of numerical computing;
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