Elementary Math For Computer Science With Python
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| Author | : Eric Bennett |
| Publisher | : Independently Published |
| Total Pages | : 192 |
| Release | : 2020-04-26 |
| Genre | : |
| ISBN | : |
Learning to code is an attractive option for many parents and elementary-aged students. Most simple computer programs, however, rely on math concepts that are not yet part of a typical, elementary school curriculum. This text solves that problem by presenting math concepts selected for their importance to computer science in a way that is accessible to a younger audience through: visual models and worked examples; thoughtfully sequenced, scaffolded practice problems; written introductions, illustrations and word problems that provide real-world context; coding examples and projects written in Python; coding challenges and extensions; solutions to all practice problems, comprehension questions and selected challenges. While many math and computer science courses equip students to complete problems by rote and copy an instructor's code, this curriculum is aimed toward facilitating the meaningful learning necessary for students to solve problems and produce original work. Note: it is recommended that students are reading at a third grade level and familiar with whole-number addition, subtraction, multiplication and division.
| Author | : Eric Lehman |
| Publisher | : |
| Total Pages | : 988 |
| Release | : 2017-03-08 |
| Genre | : Business & Economics |
| ISBN | : 9789888407064 |
This book covers elementary discrete mathematics for computer science and engineering. It emphasizes mathematical definitions and proofs as well as applicable methods. Topics include formal logic notation, proof methods; induction, well-ordering; sets, relations; elementary graph theory; integer congruences; asymptotic notation and growth of functions; permutations and combinations, counting principles; discrete probability. Further selected topics may also be covered, such as recursive definition and structural induction; state machines and invariants; recurrences; generating functions.
| Author | : Amit Saha |
| Publisher | : No Starch Press |
| Total Pages | : 265 |
| Release | : 2015-08-01 |
| Genre | : Computers |
| ISBN | : 1593277199 |
Doing Math with Python shows you how to use Python to delve into high school–level math topics like statistics, geometry, probability, and calculus. You’ll start with simple projects, like a factoring program and a quadratic-equation solver, and then create more complex projects once you’ve gotten the hang of things. Along the way, you’ll discover new ways to explore math and gain valuable programming skills that you’ll use throughout your study of math and computer science. Learn how to: –Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots –Explore set theory and probability with programs for coin flips, dicing, and other games of chance –Solve algebra problems using Python’s symbolic math functions –Draw geometric shapes and explore fractals like the Barnsley fern, the Sierpinski triangle, and the Mandelbrot set –Write programs to find derivatives and integrate functions Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You’ll write an inequality solver, plot gravity’s effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing 100,000 "darts" at a board, explore the relationship between the Fibonacci sequence and the golden ratio, and more. Whether you’re interested in math but have yet to dip into programming or you’re a teacher looking to bring programming into the classroom, you’ll find that Python makes programming easy and practical. Let Python handle the grunt work while you focus on the math. Uses Python 3
| Author | : Paul Orland |
| Publisher | : Manning Publications |
| Total Pages | : 686 |
| Release | : 2021-01-12 |
| Genre | : Computers |
| ISBN | : 1617295353 |
In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. Summary To score a job in data science, machine learning, computer graphics, and cryptography, you need to bring strong math skills to the party. Math for Programmers teaches the math you need for these hot careers, concentrating on what you need to know as a developer. Filled with lots of helpful graphics and more than 200 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest programming fields. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Skip the mathematical jargon: This one-of-a-kind book uses Python to teach the math you need to build games, simulations, 3D graphics, and machine learning algorithms. Discover how algebra and calculus come alive when you see them in code! About the book In Math for Programmers you’ll explore important mathematical concepts through hands-on coding. Filled with graphics and more than 300 exercises and mini-projects, this book unlocks the door to interesting–and lucrative!–careers in some of today’s hottest fields. As you tackle the basics of linear algebra, calculus, and machine learning, you’ll master the key Python libraries used to turn them into real-world software applications. What's inside Vector geometry for computer graphics Matrices and linear transformations Core concepts from calculus Simulation and optimization Image and audio processing Machine learning algorithms for regression and classification About the reader For programmers with basic skills in algebra. About the author Paul Orland is a programmer, software entrepreneur, and math enthusiast. He is co-founder of Tachyus, a start-up building predictive analytics software for the energy industry. You can find him online at www.paulor.land. Table of Contents 1 Learning math with code PART I - VECTORS AND GRAPHICS 2 Drawing with 2D vectors 3 Ascending to the 3D world 4 Transforming vectors and graphics 5 Computing transformations with matrices 6 Generalizing to higher dimensions 7 Solving systems of linear equations PART 2 - CALCULUS AND PHYSICAL SIMULATION 8 Understanding rates of change 9 Simulating moving objects 10 Working with symbolic expressions 11 Simulating force fields 12 Optimizing a physical system 13 Analyzing sound waves with a Fourier series PART 3 - MACHINE LEARNING APPLICATIONS 14 Fitting functions to data 15 Classifying data with logistic regression 16 Training neural networks
| Author | : Jeffrey Elkner |
| Publisher | : Samurai Media Limited |
| Total Pages | : 306 |
| Release | : 2016-10-04 |
| Genre | : Computers |
| ISBN | : 9789888406784 |
The goal of this book is to teach you to think like a computer scientist. This way of thinking combines some of the best features of mathematics, engineering, and natural science. Like mathematicians, computer scientists use formal languages to denote ideas (specifically computations). Like engineers, they design things, assembling components into systems and evaluating tradeoffs among alternatives. Like scientists, they observe the behavior of complex systems, form hypotheses, and test predictions. The single most important skill for a computer scientist is problem solving. Problem solving means the ability to formulate problems, think creatively about solutions, and express a solution clearly and accurately. As it turns out, the process of learning to program is an excellent opportunity to practice problem-solving skills. That's why this chapter is called, The way of the program. On one level, you will be learning to program, a useful skill by itself. On another level, you will use programming as a means to an end. As we go along, that end will become clearer.
| Author | : Ryan T. White |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 330 |
| Release | : 2021-02-22 |
| Genre | : Mathematics |
| ISBN | : 1838983503 |
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.
| Author | : J. C. Bautista |
| Publisher | : |
| Total Pages | : 314 |
| Release | : 2014-04 |
| Genre | : Computers |
| ISBN | : 9781291711097 |
Hemos elaborado 120 programas de Python y mas de 110 ilustraciones en una obra que sera util tanto a estudiantes de ciencias de los primeros cursos universitarios, como a estudiantes y profesores de bachillerato.Puedes descargar gratuitamente un extracto de 78 paginas del libro en pdf desde nuestro sitio web www.pysamples.com. Los compradores del libro pueden descargar gratuitamente el codigo de los programas. Todos los programas y graficas se han elaborado utilizando software libre, que se puede obtener gratuita y legalmente en internet, por lo que no es necesario adquirir ningun software. Se puede programar gratuitamente en Python tanto si eres usuario de Windows como si prefieres Mac o Linux. El libro puede ser utilizado como libro de matematicas con el que tambien se puede aprender a programar, o bien como un libro de programacion en Python orientada a las ciencias.
| Author | : Hans Petter Langtangen |
| Publisher | : Springer |
| Total Pages | : 942 |
| Release | : 2016-07-28 |
| Genre | : Computers |
| ISBN | : 3662498871 |
The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015
| Author | : Allen B. Downey |
| Publisher | : "O'Reilly Media, Inc." |
| Total Pages | : 309 |
| Release | : 2015-12-02 |
| Genre | : Computers |
| ISBN | : 1491939419 |
If you want to learn how to program, working with Python is an excellent way to start. This hands-on guide takes you through the language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. This second edition and its supporting code have been updated for Python 3. Through exercises in each chapter, youâ??ll try out programming concepts as you learn them. Think Python is ideal for students at the high school or college level, as well as self-learners, home-schooled students, and professionals who need to learn programming basics. Beginners just getting their feet wet will learn how to start with Python in a browser. Start with the basics, including language syntax and semantics Get a clear definition of each programming concept Learn about values, variables, statements, functions, and data structures in a logical progression Discover how to work with files and databases Understand objects, methods, and object-oriented programming Use debugging techniques to fix syntax, runtime, and semantic errors Explore interface design, data structures, and GUI-based programs through case studies
| Author | : Adrienne B. Tacke |
| Publisher | : Sourcebooks, Inc. |
| Total Pages | : 329 |
| Release | : 2019-03-19 |
| Genre | : Juvenile Nonfiction |
| ISBN | : 1641521767 |
Games and activities that teach kids ages 10+ to code with Python Learning to code isn't as hard as it sounds—you just have to get started! Coding for Kids: Python starts kids off right with 50 fun, interactive activities that teach them the basics of the Python programming language. From learning the essential building blocks of programming to creating their very own games, kids will progress through unique lessons packed with helpful examples—and a little silliness! Kids will follow along by starting to code (and debug their code) step by step, seeing the results of their coding in real time. Activities at the end of each chapter help test their new knowledge by combining multiple concepts. For young programmers who really want to show off their creativity, there are extra tricky challenges to tackle after each chapter. All kids need to get started is a computer and this book. This beginner's guide to Python for kids includes: 50 Innovative exercises—Coding concepts come to life with game-based exercises for creating code blocks, drawing pictures using a prewritten module, and more. Easy-to-follow guidance—New coders will be supported by thorough instructions, sample code, and explanations of new programming terms. Engaging visual lessons—Colorful illustrations and screenshots for reference help capture kids' interest and keep lessons clear and simple. Encourage kids to think independently and have fun learning an amazing new skill with this coding book for kids.
