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Mastering Python Scientific Computing
Mastering Python Scientific Computing
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Mastering Python Scientific Computing
Mastering Python Scientific Computing

El. knyga: 42,19 €

About This BookThe basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered.Most of the Python APIs and tools used in scientific computing are discussed in detailThe concepts are discussed with suitable example programsWho This Book Is ForIf you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming.What You Will…
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About This BookThe basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered.Most of the Python APIs and tools used in scientific computing are discussed in detailThe concepts are discussed with suitable example programsWho This Book Is ForIf you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming.What You Will LearnIdentify the fundamentals and components of scientific computingLearn scientific computing data managementPerform numerical computing using NumPy and SciPyDemonstrate the concepts and programming for symbolic computing using SymPyUse the matplotlib plotting library for data visualizationAnalyze data analysis and visualize it using pandas, matplotlib, and IPythonPerform parallel and high performance computingIncorporate yourself with real-life case studies and best practices of scientific computingIn Detail

In today's world, along with theoretical and experimental work, scientific computing has become an important part of scientific disciplines. A large community of users, plenty of help and documentation, a large collection of scientific libraries and environments, great performance, and good support makes Python a great choice for scientific computing.

At present, Python is among the top choices for developing scientific workflows and this book helps existing Python developers to master this domain using Python. The main things to learn in the book are the concept of scientific workflows, managing scientific workflow data, and performing computations on this data using Python.

This book discusses NumPy, SciPy, SymPy, matplotlib, pandas and IPython with several example programs.
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