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Applying Math with Python
Applying Math with Python

Applying Math with Python: Practical recipes for solving computational math problems using Python programming and its libraries

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Key benefits

  • 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

Description

Python, 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.

Who is this book for?

This 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.

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

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 31, 2020
Length: 358 pages
Edition : 1st
Language : English
ISBN-13 : 9781838986568
Category :
Languages :

What do you get with eBook?

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Product feature icon DRM FREE - Read whenever, wherever and however you want
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Product Details

Publication date : Jul 31, 2020
Length: 358 pages
Edition : 1st
Language : English
ISBN-13 : 9781838986568
Category :
Languages :

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Frequently bought together


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Total $ 121.97
Hands-On Mathematics for Deep Learning
$43.99
The Statistics and Calculus with Python Workshop
$38.99
Applying Math with Python
$38.99
Total $ 121.97 Stars icon
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Customer reviews

Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.3
(4 Ratings)
5 star 75%
4 star 0%
3 star 0%
2 star 25%
1 star 0%
Akul Sep 23, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I bought an ebook version and it’s definitely worth reading. I am an ML Practitioner and sometimes I have to scroll through tons of web pages to find the right code for solving a math problem pertaining to optimization, linear algebra and calculus but with this book, everything seems straight forward and concise. It’s a great read for those who would like to understand the math behind ML and code in python.
Amazon Verified review Amazon
Viktor Kis Aug 27, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
With a mechanical engineering background this was a 100% relatable python book for me. There are many intro to python books out there that lightly touch on a wide variety of topics for the hopes of engaging a wider audience; there will be topics of pandas and numpy followed by a chapter on web APIs. That might be great for someone that wants to know a little bit about everything but I found this book to be just right in terms of what was covered. Sure i could have bought a book just on pandas but exposure to sympy for symbolic math, scipy for integration and difEqs, matplotlib (networks), Bokeh for interactive plots was just want i wanted to see. I particularly liked the section on performance and using cython for speeding up your projects. The Monte Carlo estimating was great and also directly applicable to my work - it gave me some ideas to expand my project. The one issue i have run into in my projects is memory management, and i would have like to see some more suggestions on best practices for large projects. Overall solid book for folks working in the engineering field, and i am sure with all the examples listed it is very applicable to the financial and medical fields.
Amazon Verified review Amazon
rami krispin Nov 28, 2020
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The book provides a great introduction to Python math/stats functionality such as differential equations, probability, regression analysis, time series, and forecasting, etc. Highly recommended for R and stats people (like myself) that want to go deeper into Python.
Amazon Verified review Amazon
nh Feb 01, 2022
Full star icon Full star icon Empty star icon Empty star icon Empty star icon 2
I'm not sure about the contents - which at first glance seems a little superficial.But what is really poor is print quality. The are several pictures which are supposed to be in color, but are B&W instead.The book seems to be out of an old Xerox machine (or a poor laser office printer).Not the quality I was expecting, unfortunately.
Amazon Verified review Amazon
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