Hacking Discrete Math With Python 3
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Hacking Discrete Math With Python 3
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Author : Isabella Romeo
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2018-06-11
Hacking Discrete Math With Python 3 written by Isabella Romeo and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-06-11 with categories.
Elementary discrete math for undergraduate computer science or computer engineering students. Covers basic topics including mathematical logic, direct proof, proof by contradiction, proof by contraposition, counter-example, induction, structural induction, elementary number theory, division, sets, sequences, functions, cardinality, counting, recurrence, recursion, and graph theory. Examples are given in Python 3.
Scientific Computation
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Author : Bruce Shapiro
language : en
Publisher:
Release Date : 2018-08-20
Scientific Computation written by Bruce Shapiro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-20 with categories.
This is a book about hacking, but not just any kind of hacking. It is about mathematical hacking. If you like math and want to use computers to solve math problems, this book is for you. Scientific Computation: Python 3 Hacking for Math Junkies gives an introduction to hacking in Python for students and mathematical scientists. No previous coding experience is needed. This new edition has been updated to cover Python version 3. Computational applications are selected from many mathematical sub-disciplines. Examples include random numbers, statistics, finding roots, interpolation, linear and logistic regression, numerical solution of initial value problems, discrete systems, fractals, principal component analysis, singular value decomposition, clustering, image analysis, and satellite orbits. Over 300 exercises and projects are included for students. All code examples in the book are available for download from a companion website. The book is available in both print and electronic versions.
Scientific Computation
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Author : Bruce E. Shapiro
language : en
Publisher:
Release Date : 2015-01-11
Scientific Computation written by Bruce E. Shapiro and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-11 with Computer programming categories.
"This book is designed to help math junkies -- anyone who likes math, studies math, or uses math in their daily life -- learn about computation. The emphasis is on algorithms. It is appropriate for students with no prior programming experience as well as professional scientists. Topics covered include Python expressions, statements, types, lists, arrays, functions, classes, plotting, list comprehension, recursion, linear systems, computational geometry, root finding, interpolation, polynomial least squares, discrete systems, differential equations, principal component analysis, fractals and chaos."--Cover.
The Discrete Math Workbook
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Author : Sergei Kurgalin
language : en
Publisher: Springer Nature
Release Date : 2020-08-12
The Discrete Math Workbook written by Sergei Kurgalin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-12 with Computers categories.
This practically-focused study guide introduces the fundamentals of discrete mathematics through an extensive set of classroom-tested problems. Each chapter presents a concise introduction to the relevant theory, followed by a detailed account of common challenges and methods for overcoming these. The reader is then encouraged to practice solving such problems for themselves, by tackling a varied selection of questions and assignments of different levels of complexity. This updated second edition now covers the design and analysis of algorithms using Python, and features more than 50 new problems, complete with solutions. Topics and features: provides a substantial collection of problems and examples of varying levels of difficulty, suitable for both laboratory practical training and self-study; offers detailed solutions to each problem, applying commonly-used methods and computational schemes; introduces the fundamentals of mathematical logic, the theory of algorithms, Boolean algebra, graph theory, sets, relations, functions, and combinatorics; presents more advanced material on the design and analysis of algorithms, including Turing machines, asymptotic analysis, and parallel algorithms; includes reference lists of trigonometric and finite summation formulae in an appendix, together with basic rules for differential and integral calculus. This hands-on workbook is an invaluable resource for undergraduate students of computer science, informatics, and electronic engineering. Suitable for use in a one- or two-semester course on discrete mathematics, the text emphasizes the skills required to develop and implement an algorithm in a specific programming language.
Coding In Python And Elements Of Discrete Mathematics
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Author : Maria Litvin
language : en
Publisher:
Release Date : 2019-06-15
Coding In Python And Elements Of Discrete Mathematics written by Maria Litvin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-15 with categories.
Hacking Math Class With Python
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Author : Peter A. Farrell
language : en
Publisher: Createspace Independent Publishing Platform
Release Date : 2015-02-26
Hacking Math Class With Python written by Peter A. Farrell and has been published by Createspace Independent Publishing Platform this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-26 with categories.
A new kind of math book! Explore math topics from arithmetic to calculus by creating your own graphing and solving tools using Python. Create 2D and 3D graphics, harmonograph and spirograph designs, and fractals in this interactive and visual exploration of mathematics. "A great resource to play with Math and Python via the turtle module, solving equations numerically and 3D graphics via Pi3D." - Amit Saha, author of Doing Math With Python Imagine learning math and Python programming at the same time! You'll learn to use loops, variables, functions, conditionals and lists and apply them to all your math problems. No previous computer experience is required.
The Statistics And Calculus With Python Workshop
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Author : Peter Farrell
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-08-18
The Statistics And Calculus With Python Workshop written by Peter Farrell and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-18 with Computers categories.
With examples and activities that help you achieve real results, applying calculus and statistical methods relevant to advanced data science has never been so easy Key FeaturesDiscover how most programmers use the main Python libraries when performing statistics with PythonUse descriptive statistics and visualizations to answer business and scientific questionsSolve complicated calculus problems, such as arc length and solids of revolution using derivatives and integralsBook Description Are you looking to start developing artificial intelligence applications? Do you need a refresher on key mathematical concepts? Full of engaging practical exercises, The Statistics and Calculus with Python Workshop will show you how to apply your understanding of advanced mathematics in the context of Python. The book begins by giving you a high-level overview of the libraries you'll use while performing statistics with Python. As you progress, you'll perform various mathematical tasks using the Python programming language, such as solving algebraic functions with Python starting with basic functions, and then working through transformations and solving equations. Later chapters in the book will cover statistics and calculus concepts and how to use them to solve problems and gain useful insights. Finally, you'll study differential equations with an emphasis on numerical methods and learn about algorithms that directly calculate values of functions. By the end of this book, you'll have learned how to apply essential statistics and calculus concepts to develop robust Python applications that solve business challenges. What you will learnGet to grips with the fundamental mathematical functions in PythonPerform calculations on tabular datasets using pandasUnderstand the differences between polynomials, rational functions, exponential functions, and trigonometric functionsUse algebra techniques for solving systems of equationsSolve real-world problems with probabilitySolve optimization problems with derivatives and integralsWho this book is for If you are a Python programmer who wants to develop intelligent solutions that solve challenging business problems, then this book is for you. To better grasp the concepts explained in this book, you must have a thorough understanding of advanced mathematical concepts, such as Markov chains, Euler's formula, and Runge-Kutta methods as the book only explains how these techniques and concepts can be implemented in Python.
Practical Discrete Mathematics
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Author : Ryan T. White
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-02-22
Practical Discrete Mathematics written by Ryan T. White and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-22 with Mathematics categories.
A practical guide simplifying discrete math for curious minds and demonstrating its application in solving problems related to software development, computer algorithms, and data science Key FeaturesApply the math of countable objects to practical problems in computer scienceExplore modern Python libraries such as scikit-learn, NumPy, and SciPy for performing mathematicsLearn complex statistical and mathematical concepts with the help of hands-on examples and expert guidanceBook Description Discrete mathematics deals with studying countable, distinct elements, and its principles are widely used in building algorithms for computer science and data science. The knowledge of discrete math concepts will help you understand the algorithms, binary, and general mathematics that sit at the core of data-driven tasks. Practical Discrete Mathematics is a comprehensive introduction for those who are new to the mathematics of countable objects. This book will help you get up to speed with using discrete math principles to take your computer science skills to a more advanced level. As you learn the language of discrete mathematics, you'll also cover methods crucial to studying and describing computer science and machine learning objects and algorithms. The chapters that follow will guide you through how memory and CPUs work. In addition to this, you'll understand how to analyze data for useful patterns, before finally exploring how to apply math concepts in network routing, web searching, and data science. By the end of this book, you'll have a deeper understanding of discrete math and its applications in computer science, and be ready to work on real-world algorithm development and machine learning. What you will learnUnderstand the terminology and methods in discrete math and their usage in algorithms and data problemsUse Boolean algebra in formal logic and elementary control structuresImplement combinatorics to measure computational complexity and manage memory allocationUse random variables, calculate descriptive statistics, and find average-case computational complexitySolve graph problems involved in routing, pathfinding, and graph searches, such as depth-first searchPerform ML tasks such as data visualization, regression, and dimensionality reductionWho this book is for This book is for computer scientists looking to expand their knowledge of discrete math, the core topic of their field. University students looking to get hands-on with computer science, mathematics, statistics, engineering, or related disciplines will also find this book useful. Basic Python programming skills and knowledge of elementary real-number algebra are required to get started with this book.
Numerical Methods In Engineering With Python 3
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Author : Jaan Kiusalaas
language : en
Publisher: Cambridge University Press
Release Date : 2013-01-21
Numerical Methods In Engineering With Python 3 written by Jaan Kiusalaas and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-01-21 with Computers categories.
Provides an introduction to numerical methods for students in engineering. It uses Python 3, an easy-to-use, high-level programming language.
Discrete Mathematical Algorithm And Data Structures
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Author : Sanjib Sinha
language : en
Publisher:
Release Date : 2020-05-28
Discrete Mathematical Algorithm And Data Structures written by Sanjib Sinha and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-28 with categories.
Readers will learn discrete mathematical abstracts as well as its implementation in algorithm and data structures shown in various programming languages, such as C, C++, PHP, Java, C#, Python and Dart. This book combines two major components of Mathematics and Computer Science under one roof. Without the core conceptions and tools derived from discrete mathematics, one cannot understand the abstract or the general idea involving algorithm and data structures in Computer Science. The objects of data structures are basically objects of discrete mathematics. This book tries to bridge the gap between two major components of Mathematics and Computer Science.In any computer science course, studying discrete mathematics is essential, although they are taught separately, except in a few cases. Yet, a comprehensive book, combining these two major components, is hard to find out; not only that, it is almost impossible to understand one without the help of other.Hope, this book will fill the gap. Readers will learn discrete mathematical abstracts as well as its implementation in algorithm and data structures shown in various programming language, such as C++, Java, C#, Python and Dart.1. Introduction to the Discourse Is Discrete Mathematics enough to study Computer Science? A short Introduction to Discrete Mathematics What is Discrete Mathematics What is the relationship between Discrete Mathematics and Computer Science Introducing necessary conceptions 2. Introduction to Programming Language and Boolean Algebra Logic, Mathematics, and Programming Language Introduction to Boolean Algebra 3. De Morgan's Laws on Boolean Algebra, Logical Expression, and Algorithm Logical Expression Short Circuit Evaluation Syntax, Semantics and Conditional Execution Why we need Control Constructs Discrete Mathematical Notations and Algorithm 4. Data Structures in different Programming languages Mean, Median and Mode Array, the First Step to Data Structure Let us understand some Array features Set Theory, Probability and Array Skewed Mean, Maximized Median Complex Array Algorithm 5. Data Structures: Abstractions and Implementation How objects work with each other More Algorithm and Time Complexity Introducing Data Structures How Calculus and Linear Algebra are Related to this Discourse 6. Data Structures in Detail Frequently Asked Questions about Data Structures Abstract Data Type (ADT) Linear Data Structures Modeling of a Structure ArrayList to overcome limitations of Array ArrayList or LinkedList, which is faster? Collection Framework in programming languages Stack and Queue in Java Deque, a high-performance Abstract Data Type 7. Algorithm, Data Structure, Collection Framework and Standard Template Library (STL) Introducing Algorithm Library Different types of Algorithms Binary Tree and Data Structure Collection Framework in Java Discrete Mathematical Abstractions and Implementation through Java Collection Comparator, Comparable and Iterator Standard Template Library in C++ 8. Time Complexity Order of n, or O(n) Big O Notation 9. Set, Symmetric Difference and Propositional Logic Why Set is important in Data Structures How Symmetric Difference and Propositional Logic combine 10. Combinatorics and Counting, Permutation and Combinations Permutation and Combination What Next