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Mastering Python Scientific Computing - Hemant Kumar Mehta pdf

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Description

 							
  
  A complete guide for Python
programmers to master scientific computing using Python APIs and tools
  
  About This Book
  The
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 detail 
  The concepts are
discussed with suitable example programs
  
  Who This Book Is For
  If 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 Learn
  Fundamentals and
components of scientific computing 
  Scientific computing data management 
  Performing numerical computing
using NumPy and SciPy 
  Concepts and programming for symbolic computing using SymPy 
  Using the plotting
library matplotlib for data visualization 
  Data analysis and visualization using Pandas, matplotlib, and IPython

  Performing parallel and high performance computing 
  Real-life case studies and best practices of
scientific computing
  
  In Detail
  In today's world, along with theoretical and experimental
work, scientific computing has become an important part of scientific disciplines. Numerical calculations, simulations
and computer modeling in this day and age form the vast majority of both experimental and theoretical papers. In the
scientific method, replication and reproducibility are two important contributing factors. A complete and concrete
scientific result should be reproducible and replicable. Python is suitable for scientific computing. 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 workflow and the book targets existing Python developers to master this domain
using Python. The main things to learn in the book are the concept of scientific workflow, managing scientific workflow
data and performing computation on this data using Python.
  The book discusses NumPy, SciPy, SymPy, matplotlib,
Pandas and IPython with several example programs. 						

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