Download or read book Hacking Discrete Math With Python 3 written by Isabella Romeo and published by Createspace Independent Publishing Platform. This book was released on 2018-06-11 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Scientific Computation written by Bruce Shapiro and published by . This book was released on 2018-08-20 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Scientific Computation written by Bruce E. Shapiro and published by . This book was released on 2015-01-11 with total page 458 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.

Download or read book The Discrete Math Workbook written by Sergei Kurgalin and published by Springer Nature. This book was released on 2020-08-12 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Practical Discrete Mathematics written by Ryan T. White and published by Packt Publishing Ltd. This book was released on 2021-02-22 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Hacking Math Class with Python written by Peter A. Farrell and published by Createspace Independent Publishing Platform. This book was released on 2015-02-26 with total page 144 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Hacking Python 3 written by Sanjib Sinha and published by . This book was released on 2017-03-11 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Have you seen the film "The Matrix Reloaded"? Well, if you had seen you would have probably recalled the scene where the character Trinity was seen using NMAP to hack the system of a power plant. This book is all about Scanning, Networking and Information Gathering with the help of Python programming language and by the way teaches you major steps of Ethical Hacking.Contents:# Epilogue# PART ONE: LEGAL SIDE, CYBER CRIME AND NETWORKING# Chapter 1 - Legal Side of Hacking# Chapter 2 - Examples of Crime## 2.1 - Black Money and Bitcoin## 2.2 The Great Cyber Robberies ## 2.3 - Biggest Data Heist## 2.4 - Internet: Battleground for Women# Chapter 3 - Hacking and Networking## 3.1 - What Does Network Mean?#PART TWO: PYTHON AND HACKING# Chapter 4 - Object in Python# Chapter 5 - Conditionals# Chapter 6 - Loops## 6.1 - While Loops## 6.2 - For Loops# Chapter 7 - Regular Expressions ## 7.1 - Using 're' Module## 7.2 - Reusing With Regular Expressions## 7.3 - Search With Regular Expressions# Chapter 8. - Exceptions, Errors# Chapter 9 - Functions## 9.1 - Return Values## 9.2 - Generate Functions## 9.3 - Lists of Arguments## 9.4 - Named Arguments# Chapter 10 - Classes## 10.1 - Object Oriented Methodology## 10.2 - Classes and Objects## 10.3 - Write a Game "Good VS Bad"## 10.4 - Primary Class and Object## 10.5 - Accessing Object Data## 10.6 - Polymorphism## 10.7 - Using Generators## 10.8 -Decorator# Chapter 11 - File Input, Output# Chapter 12 - Containers## 12.1 - Tuple and List Object## 12.2 - Dictionary Object# Chapter 13 - Module# Chapter 14 - Debugging, UnitTestChapter 15 - Socket and Networking# Chapter 16 - Importing Nmap Module# Chapter 17 - Nmap Network Scanner#PART THREE: PYTHON AND SECURITY ANALYSIS, RECONNAISSANCE SCANNER# Chapter 18 - TLD Scanner# Chapter 19 - Get IP Address# Chapter 20 - Whois Search# Chapter 21 - NMAP Port Scan# Chapter 22 - Robots Exclusion# Prologue

Download or read book Coding in Python and Elements of Discrete Mathematics written by Maria Litvin and published by . This book was released on 2019-06-15 with total page 420 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Discrete Mathematical Algorithm and Data Structures written by Sanjib Sinha and published by . This book was released on 2020-05-28 with total page 650 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Programming and Mathematical Thinking written by and published by . This book was released on 2014 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: Concepts of discrete mathematics can help clarify a programmer's thinking about software design problems and can make many solutions obvious. Starting at an elementary level, this book teaches about fundamental structures of discrete mathematics together with many simple but powerful programming techniques using those structures.

Download or read book Python for Scientists written by John M. Stewart and published by Cambridge University Press. This book was released on 2017-07-20 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific Python is taught from scratch in this book via copious, downloadable, useful and adaptable code snippets. Everything the working scientist needs to know is covered, quickly providing researchers and research students with the skills to start using Python effectively.

Download or read book Math Adventures with Python written by Peter Farrell and published by No Starch Press. This book was released on 2019-01-08 with total page 305 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn math by getting creative with code! Use the Python programming language to transform learning high school-level math topics like algebra, geometry, trigonometry, and calculus! Math Adventures with Python will show you how to harness the power of programming to keep math relevant and fun. With the aid of the Python programming language, you'll learn how to visualize solutions to a range of math problems as you use code to explore key mathematical concepts like algebra, trigonometry, matrices, and cellular automata. Once you've learned the programming basics like loops and variables, you'll write your own programs to solve equations quickly, make cool things like an interactive rainbow grid, and automate tedious tasks like factoring numbers and finding square roots. You'll learn how to write functions to draw and manipulate shapes, create oscillating sine waves, and solve equations graphically. You'll also learn how to: - Draw and transform 2D and 3D graphics with matrices - Make colorful designs like the Mandelbrot and Julia sets with complex numbers - Use recursion to create fractals like the Koch snowflake and the Sierpinski triangle - Generate virtual sheep that graze on grass and multiply autonomously - Crack secret codes using genetic algorithms As you work through the book's numerous examples and increasingly challenging exercises, you'll code your own solutions, create beautiful visualizations, and see just how much more fun math can be!

Download or read book Scientific Computation written by Bruce Shapiro and published by . This book was released on 2018-07 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientific computation using Python 3 and the Jupyter notebook. Earlier editions were sub-titled "Python Hacking for Math Junkies" and covered only Python 2. This version is updated to cover Python Version 3.

Download or read book Mathematics for Machine Learning written by Marc Peter Deisenroth and published by Cambridge University Press. This book was released on 2020-04-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book's web site.

Download or read book Data Science and Machine Learning written by Dirk P. Kroese and published by CRC Press. This book was released on 2019-11-20 with total page 538 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focuses on mathematical understanding Presentation is self-contained, accessible, and comprehensive Full color throughout Extensive list of exercises and worked-out examples Many concrete algorithms with actual code

Download or read book Practical Cryptography in Python written by Seth James Nielson and published by Apress. This book was released on 2019-09-27 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop a greater intuition for the proper use of cryptography. This book teaches the basics of writing cryptographic algorithms in Python, demystifies cryptographic internals, and demonstrates common ways cryptography is used incorrectly. Cryptography is the lifeblood of the digital world’s security infrastructure. From governments around the world to the average consumer, most communications are protected in some form or another by cryptography. These days, even Google searches are encrypted. Despite its ubiquity, cryptography is easy to misconfigure, misuse, and misunderstand. Developers building cryptographic operations into their applications are not typically experts in the subject, and may not fully grasp the implication of different algorithms, modes, and other parameters. The concepts in this book are largely taught by example, including incorrect uses of cryptography and how "bad" cryptography can be broken. By digging into the guts of cryptography, you can experience what works, what doesn't, and why. What You’ll Learn Understand where cryptography is used, why, and how it gets misused Know what secure hashing is used for and its basic propertiesGet up to speed on algorithms and modes for block ciphers such as AES, and see how bad configurations breakUse message integrity and/or digital signatures to protect messagesUtilize modern symmetric ciphers such as AES-GCM and CHACHAPractice the basics of public key cryptography, including ECDSA signaturesDiscover how RSA encryption can be broken if insecure padding is usedEmploy TLS connections for secure communicationsFind out how certificates work and modern improvements such as certificate pinning and certificate transparency (CT) logs Who This Book Is For IT administrators and software developers familiar with Python. Although readers may have some knowledge of cryptography, the book assumes that the reader is starting from scratch.

Download or read book The Statistics and Calculus with Python Workshop written by Peter Farrell and published by Packt Publishing Ltd. This book was released on 2020-08-18 with total page 739 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.