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Math for Deep Learning: What You Need to Know to Understand Neural Networks
by Ronald T. KneuselMath for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the deep learning toolkits.With Math for Deep Learning, you'll learn the essential mathematics used by and as a background for deep learning. You&’ll work through Python examples to learn key deep learning related topics in probability, statistics, linear algebra, differential calculus, and matrix calculus as well as how to implement data flow in a neural network, backpropagation, and gradient descent. You&’ll also use Python to work through the mathematics that underlies those algorithms and even build a fully-functional neural network.In addition you&’ll find coverage of gradient descent including variations commonly used by the deep learning community: SGD, Adam, RMSprop, and Adagrad/Adadelta.
Math for English Majors: A Human Take on the Universal Language
by Ben OrlinIn this trailblazing work from the internet&’s most empathetic math teacher, Ben Orlin unravels the secrets behind the world&’s most confounding language. Math, it is said, is the "universal language.&” But if a language brings people together, why does math make so many of us feel so alone? In Math for English Majors, bestselling author Ben Orlin (Math with Bad Drawings) offers fresh insights for the mathematically perplexed and mathematical masters alike. As Orlin reveals, the &“universal language&” is precisely that: a language. It has nouns (numbers), verbs (calculations), and grammar (algebra). It has funny idioms (&“exponential&”), quirky etymologies (&“squaring&”), and peculiar ambiguities (&“PEMDAS&”). It even has its own form of literature, with equations ranging from the simple wisdom of A2 + B2 = C2 to the startling profundity of eπi + 1 = 0. Along the way, he shares relatable stories of his own mathematical misunderstandings and epiphanies, as well as the trials and triumphs of his students. And, as always, he sheds further light and levity on the subject with his inept—yet strangely effective—drawings.
Math for Financial Literacy
by Todd Knowlton Paul Gray Jr.This book prepares your students for the real world. Written specifically for teens, Math for Financial Literacy provides instruction for relevant math concepts that students can easily relate to their daily lives. <p><p> In Math for Financial Literacy, students learn how to apply basic math concepts to the tasks they will use in the real world, including earning a paycheck, managing a bank account, using credit cards, and creating a budget. Other practical topics are presented to help students become financially capable and responsible. Each chapter is designed to present content in small segments for optimal comprehension.
Math for Meds: Dosages and Solutions (10th Edition)
by Anna M. CurrenIncrease your confidence and aptitude in dosage calculations with the best-selling ratio and proportion book on the market! Learn from the master, Anna Curren, who has successfully taught dosage calculations to thousands of students. This new edition of Math for Meds includes full-color drug labels and syringes throughout, which are tied to questions that test your understanding and mastery of the concepts. With the goal of helping you become a safe and effective practitioner, Math for Meds walks you through basic and advanced calculations in detail, including intravenous and pediatric calculations.
Math for Programmers: 3D graphics, machine learning, and simulations with Python
by Paul OrlandIn 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
Math for Programming
by Ronald T. KneuselA one-stop-shop for all the math you should have learned for your programming career.Every great programming challenge has mathematical principles at its heart. Whether you&’re optimizing search algorithms, building physics engines for games, or training neural networks, success depends on your grasp of core mathematical concepts. In Math for Programming, you&’ll master the essential mathematics that will take you from basic coding to serious software development. You&’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms.Through clear explanations and practical examples, you&’ll learn to:Harness linear algebra to manipulate data with unprecedented efficiencyApply calculus concepts to optimize algorithms and drive simulationsUse probability and statistics to model uncertainty and analyze dataMaster the discrete mathematics that powers modern data structuresSolve dynamic problems through differential equationsWhether you&’re seeking to fill gaps in your mathematical foundation or looking to refresh your understanding of core concepts, Math for Programming will turn complex math into a practical tool you&’ll use every day.
Math for Scientists: Refreshing the Essentials
by Natasha Maurits Branislava Ćurčić-BlakeThis book reviews math topics relevant to non-mathematics students and scientists, but which they may not have seen or studied for a while. These math issues can range from reading mathematical symbols, to using complex numbers, dealing with equations involved in calculating medication equivalents, the General Linear Model (GLM) used in e.g. neuroimaging analysis, finding the minimum of a function, independent component analysis, or filtering approaches. Almost every student or scientist, will at some point run into mathematical formulas or ideas in scientific papers that may be hard to understand, given that formal math education may be some years ago. In this book we will explain the theory behind many of these mathematical ideas and expressions and provide readers with the tools to better understand them. We will revisit high school mathematics and extend and relate this to the mathematics you need to understand the math you may encounter in the course of your research. This book will help you understand the math and formulas in the scientific papers you read. To achieve this goal, each chapter mixes theory with practical pen-and-paper exercises such that you (re)gain experience with solving math problems yourself. Mnemonics will be taught whenever possible. To clarify the math and help readers apply it, each chapter provides real-world and scientific examples.In this new edition, two new chapters covering statistics and differential equations have been added, which have been workshopped in the 'authors' popular lecture series in order to maximize the benefit for readers.
Math for Security: From Graphs and Geometry to Spatial Analysis
by Daniel ReillyUse applied math to map fire stations, develop facial recognition software, solve the art gallery problem and more in this hands-on, real-world infosec book.Explore the intersection of mathematics and computer security with this engaging and accessible guide.Math for Security will equip you with essential tools to tackle complex security problems head on. All you need are some basic programming skills. Once you&’ve set up your development environment and reviewed the necessary Python syntax and math notation in the early chapters, you&’ll dive deep into practical applications, leveraging the power of math to analyze networks, optimize resource distribution, and much more. In the book&’s final chapters, you&’ll take your projects from proof of concepts to viable applications and explore options for delivering them to end users.As you work through various security scenarios, you&’ll:Employ packet analysis and graph theory to detect data exfiltration attempts in a networkPredict potential targets and find weaknesses in social networks with Monte Carlo simulationsUse basic geometry and OpenCell data to triangulate a phone&’s location without GPSApply computational geometry to Voronoi diagrams for use in emergency service planningTrain a facial recognition system with machine learning for real-time identity verificationUse spatial analysis to distribute physical security features effectively in an art galleryWhether you&’re an aspiring security professional, a social network analyst, or an innovator seeking to create cutting-edge security solutions, this book will empower you to solve complex problems with precision and confidence. Embrace the intricate world of math as your secret weapon in computer security!Covers Python 3.x
Math for the Automotive Trade
by John C. Peterson William J. DekrygerMATH FOR THE AUTOMOTIVE TRADE, 5E is an up-to-date, highly practical book that helps readers develop a real-world understanding of math concepts and applications in the modern automotive repair trade. Written at a beginner's level, this book is a comprehensive instructional workbook that shows readers how to solve the types of math problems faced regularly by automotive technicians. Unique to MATH FOR THE AUTOMOTIVE TRADE, 5E are realistic practice exercises that allow readers to determine if their answers fall within manufacturers' specifications and repair orders that are completed by finding the appropriate information in the professional literature and reference material, included in the book's valuable appendices.
Math for the Pharmacy Technician: Concepts and Calculations
by Kathryn A. Booth Lynn M. EglerRecognizing the enormous need for well-trained pharmacy technicians as well as the serious need to decrease medication errors, we have developed Math for Pharmacy Technicians: Concepts and Calculations. This textbook is organized from simple to complex and walks the student through the necessary information to pass the math portion of the Pharmacy Technician Certification Board (PTCB) exam. More important, we have created pharmacy technician-specific information that is nonthreatening and will help the student learn to safely practice as a pharmacy technician. This text is organized into 11 chapters, along with a pretest and a comprehensive evaluation, or post test.
Math for the Professional Kitchen
by The Culinary Institute of America Laura Dreesen Michael Nothnagel Susan WysockiThe book is a valuable resource not only in the classroom but also in the kitchen as students embark on their professional careers, where math skills play a crucial role in the ever-important bottom line.
Math in EPUB Advanced Testbook
by Math Task ForceThis is a test of MathML in EPUB, including MathML with Image Fallback tests
Math in Focus: The Singapore Approach (Student Book 5B)
by Fong Ho Kheong Chelvi Ramakrishnan Gan Kee SoonThe book helps students learn important new concepts by combining logical thinking with math skills, to meet new problem-solving challenges.
Math in FocusTM: The Singapore Approach, Workbook, 5B
by Fong Ho Kheong Chelvi Ramakrishnan Gan Kee SoonNIMAC-sourced textbook
Math in Focus®: Student Edition Volume A Grade 2 2020
by Fong Ho Kheong Chelvi Ramakrishnan Michelle ChooNIMAC-sourced textbook
Math in Focus®: Student Edition Volume B Grade 2 2020
by Fong Ho Kheong Chelvi Ramakrishnan Michelle ChooNIMAC-sourced textbook
Math in Focus®: Student Edition, Book A Grade 3 2018
by Fong Ho Kheong Chelvi Ramakrishnan Bernice Lau Pui WahNIMAC-sourced textbook
Math in Focus®: Student Workbook, Book A Grade 3
by Fong Ho Kheong Chelvi Ramakrishnan Michelle ChooNIMAC-sourced textbook
Math in Minutes
by Paul GlendinningBoth simple and accessible, Math in Minutes is a visually led introduction to 200 key mathematical ideas. Each concept is quick and easy to remember, described by means of an easy-to-understand picture and a maximum 200-word explanation.Concepts span all of the key areas of mathematics, including Fundamentals of Mathematics, Sets and Numbers, Geometry, Equations, Limits, Functions and Calculus, Vectors and Algebra, Complex Numbers, Combinatorics, Number Theory, Metrics and Measures and Topology.From the Trade Paperback edition.
Math in Our World
by Allan G. Bluman Dave Sobecki"Mathematics in Our World" is designed for mathematics survey courses for non-science majors. <p><p> The text covers a variety of topics designed to foster interest in and show the applicability of mathematics. The book is written by our successful statistics author, Allan Bluman. His easy-going writing style and step-by-step approach make this text very readable and accessible to lower-level students. The text contains many pedagogical features designed to both aid the student and instill a sense that mathematics is not just adding and subtracting.
Math in Our World: A Quantitative Literacy Approach
by Dave Sobecki Brian MercerWhat does quantitative reasoning really mean? Is it just liberal arts math with a new name on the cover of the book? We say that it is not. It’s about students productively struggling with context-based problems. It’s not just learning how to do math problems, but more importantly learning how quantitative thinking is applied throughout the curriculum, and throughout a lifetime.
Math in Our World: A Quantitative Reasoning Approach
by Dave Sobecki Brian MercerMath in Our World: A Quantitative Reasoning Approach
Math in Society Edition 2.2
by David LippmanMath in Society is a survey of contemporary mathematical topics, appropriate for a college-level topics course for liberal arts major, or as a general quantitative reasoning course.
Math in the Time of Corona (Mathematics Online First Collections)
by Alice WondersThe title of this book, Math in the Time of Corona, has been drawn from the highly acclaimed novel by Gabriel García Márquez, Love in the Time of Cholera. The volume editor, Alice Wonders, holds a fictitious name that represents the mathematics publishing group at Springer Nature. Undeterred by disasters, so many mathematical and scientific discoveries have been made during times of duress or confinement. Unlike most any other subject, mathematics may be researched from anywhere. Covid-19, like Cholera, implementation of vaccinations have been uneven throughout the globe since the beginning of 2021. However, there has been a renewed hope for a return to normalcy though the timing will no doubt vary worldwide. Essays in this volume vary in topic and are written by members of the greater mathematics community, hence the use of “Math” in the book title. They recount or describe significant or noteworthy discoveries, musings, award winnings, eureka moments, challenges, solutions, inspirations, etc. that have resulted from, or have occurred during, an unprecedented global pandemic. Several of the authors have been involved in starting new research and devising new methodologies related to society’s response to the outbreak and its ability to self-organize during a dramatic and complex situation. Some contributions describe how mathematical models and the management of big data have proved to be fundamental tools for the interpretation of epidemic activity and development of coping mechanisms.