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Applying Math with Python

Applying Math with Python

By : Sam Morley
4.3 (4)
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Applying Math with Python

Applying Math with Python

4.3 (4)
By: Sam Morley

Overview of this book

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.
Table of Contents (12 chapters)
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Working with Trees and Networks

Networks are objects that contain nodesand edges between pairs of nodes. They can be used to represent a wide variety of real-world situations, such as distribution and scheduling. Mathematically, networks are useful for visualizing combinatorial problems and make for a rich and fascinating theory.

There are, of course, several different kinds of networks. We will mostly deal with simple networks, where edges connect two distinct nodes (so there are no self-loops), there is, at most, one edge between any two nodes, and all the edges are bidirectional. A treeis a special kind of network in which there are no cycles; that is, there are no lists of nodes in which each node is connected to the following node by an edge, and the final node is connected to the first. Trees are especially simple in terms of their theory because they connect a number of nodes with the fewest possible edges. A complete...

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Applying Math with Python
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