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Applying Math with Python - Practical recipes for solving computational math problems using Python programming and its libraries (Paperback)
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Applying Math with Python - Practical recipes for solving computational math problems using Python programming and its libraries (Paperback)
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Discover easy-to-follow solutions and techniques to help you to
implement applied mathematical concepts such as probability,
calculus, and equations using Python's numeric and scientific
libraries Key Features Compute complex mathematical problems using
programming logic with the help of step-by-step recipes Learn how
to utilize Python's libraries for computation, mathematical
modeling, and statistics Discover simple yet effective techniques
for solving mathematical equations and apply them in real-world
statistics Book DescriptionPython, one of the world's most popular
programming languages, has a number of powerful packages to help
you tackle complex mathematical problems in a simple and efficient
way. These core capabilities help programmers pave the way for
building exciting applications in various domains, such as machine
learning and data science, using knowledge in the computational
mathematics domain. The book teaches you how to solve problems
faced in a wide variety of mathematical fields, including calculus,
probability, statistics and data science, graph theory,
optimization, and geometry. You'll start by developing core skills
and learning about packages covered in Python's scientific stack,
including NumPy, SciPy, and Matplotlib. As you advance, you'll get
to grips with more advanced topics of calculus, probability, and
networks (graph theory). After you gain a solid understanding of
these topics, you'll discover Python's applications in data science
and statistics, forecasting, geometry, and optimization. The final
chapters will take you through a collection of miscellaneous
problems, including working with specific data formats and
accelerating code. By the end of this book, you'll have an arsenal
of practical coding solutions that can be used and modified to
solve a wide range of practical problems in computational
mathematics and data science. What you will learn Get familiar with
basic packages, tools, and libraries in Python for solving
mathematical problems Explore various techniques that will help you
to solve computational mathematical problems Understand the core
concepts of applied mathematics and how you can apply them in
computer science Discover how to choose the most suitable package,
tool, or technique to solve a certain problem Implement basic
mathematical plotting, change plot styles, and add labels to the
plots using Matplotlib Get to grips with probability theory with
the Bayesian inference and Markov Chain Monte Carlo (MCMC) methods
Who this book is forThis book is for professional programmers and
students looking to solve mathematical problems computationally
using Python. Advanced mathematics knowledge is not a requirement,
but a basic knowledge of mathematics will help you to get the most
out of this book. The book assumes familiarity with Python concepts
of data structures.
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