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Machine Learning For Kids
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Book Synopsis Machine Learning for Kids by : Dale Lane
Download or read book Machine Learning for Kids written by Dale Lane and published by No Starch Press. This book was released on 2021-01-19 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on, application-based introduction to machine learning and artificial intelligence (AI) that guides young readers through creating compelling AI-powered games and applications using the Scratch programming language. Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based, award-winning companion website, you'll see how easy it is to add machine learning to your own projects. You don't even need to know how to code! As you work through the book you'll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve their accuracy. You'll turn your models into fun computer games and apps, and see what happens when they get confused by bad data. You'll build 13 projects step-by-step from the ground up, including: • Rock, Paper, Scissors game that recognizes your hand shapes • An app that recommends movies based on other movies that you like • A computer character that reacts to insults and compliments • An interactive virtual assistant (like Siri or Alexa) that obeys commands • An AI version of Pac-Man, with a smart character that knows how to avoid ghosts NOTE: This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project. Ages 12+
Book Synopsis Machine Learning for Babies & Toddlers (Tinker Toddlers) by : Dr Dhoot
Download or read book Machine Learning for Babies & Toddlers (Tinker Toddlers) written by Dr Dhoot and published by . This book was released on 2019-02-08 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simple concepts about up-and-coming science and technology to kick-start your future genius! Machine Learning for Babies & Toddlers is a great way to introduce basic concepts about machine learning, an exploding field that will be like electricity to our future generation. Familiarize your little one with what machines are and they can learn, just like us! The colorful, beautiful, and visually stimulating illustrations encourage the child's sense of wonder and curiosity (and might stimulate your senses too)! Levels of learning: Level 1 baby basics in black text and Level 2 in purple text for toddlers to build on. Look for other books by Tinker Toddlers(TM) Artificial Intelligence for Babies & Toddlers and Solar System for Babies & Toddlers
Book Synopsis Machine Learning for Kids by : Dale Lane
Download or read book Machine Learning for Kids written by Dale Lane and published by No Starch Press. This book was released on 2021-02-09 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: A hands-on, application-based introduction to machine learning and artificial intelligence (AI). Create compelling AI-powered games and applications using the Scratch programming language. AI Made Easy with 13 Projects Machine learning (also known as ML) is one of the building blocks of AI, or artificial intelligence. AI is based on the idea that computers can learn on their own, with your help. Machine Learning for Kids will introduce you to machine learning, painlessly. With this book and its free, Scratch-based companion website, you’ll see how easy it is to add machine learning to your own projects. You don’t even need to know how to code! Step by easy step, you’ll discover how machine learning systems can be taught to recognize text, images, numbers, and sounds, and how to train your models to improve them. You’ll turn your models into 13 fun computer games and apps, including: A Rock, Paper, Scissors game that recognizes your hand shapes A computer character that reacts to insults and compliments An interactive virtual assistant (like Siri or Alexa) A movie recommendation app An AI version of Pac-Man There’s no experience required and step-by-step instructions make sure that anyone can follow along! No Experience Necessary! Ages 12+
Book Synopsis Eric Is Thirsty: Machine Learning for Kids: Gradient Descent by : Rocket Baby Club
Download or read book Eric Is Thirsty: Machine Learning for Kids: Gradient Descent written by Rocket Baby Club and published by Rocket Baby Club. This book was released on 2019-01-21 with total page 36 pages. Available in PDF, EPUB and Kindle. Book excerpt: Eric the ladybug is an artist and traveler. He went to a mountain to watch the sunset and drew a painting of it. The next day when he woke up, he feels so thirsty and needs to find some water to drink. Will he be able to find the lowest point near him in order to find a water source? After an adventure with Eric the thirsty ladybug, you will know the most important intuition in machine learning, gradient descent.
Book Synopsis Neural Networks for Babies by : Chris Ferrie
Download or read book Neural Networks for Babies written by Chris Ferrie and published by Sourcebooks, Inc.. This book was released on 2019-03-01 with total page 26 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fans of Chris Ferrie's ABCs of Economics, ABCs of Space, and Organic Chemistry for Babies will love this introduction to neural networks for babies and toddlers! Help your future genius become the smartest baby in the room! It only takes a small spark to ignite a child's mind. Neural Networks for Babies by Chris Ferrie is a colorfully simple introduction to the study of how machines and computing systems are created in a way that was inspired by the biological neural networks in animal and human brains. With scientific and mathematical information from an expert, this installment of the Baby University board book series is the perfect book for enlightening the next generation of geniuses. After all, it's never too early to become a scientist! If you're looking for programming for babies, coding for babies, or more Baby University board books to surprise your little one, look no further! Neural Networks for Babies offers fun early learning for your little scientist!
Book Synopsis Machine Learning For Dummies by : John Paul Mueller
Download or read book Machine Learning For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2021-02-09 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of Mark Cuban’s top reads for better understanding A.I. (inc.com, 2021) Your comprehensive entry-level guide to machine learning While machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie Ex Machina—it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models—and way, way more. Unlike most machine learning books, the fully updated 2nd Edition of Machine Learning For Dummies doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study. Understand the history of AI and machine learning Work with Python 3.8 and TensorFlow 2.x (and R as a download) Build and test your own models Use the latest datasets, rather than the worn out data found in other books Apply machine learning to real problems Whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.
Book Synopsis The Art of Machine Learning by : Norman Matloff
Download or read book The Art of Machine Learning written by Norman Matloff and published by No Starch Press. This book was released on 2024-01-09 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to expertly apply a range of machine learning methods to real data with this practical guide. Packed with real datasets and practical examples, The Art of Machine Learning will help you develop an intuitive understanding of how and why ML methods work, without the need for advanced math. As you work through the book, you’ll learn how to implement a range of powerful ML techniques, starting with the k-Nearest Neighbors (k-NN) method and random forests, and moving on to gradient boosting, support vector machines (SVMs), neural networks, and more. With the aid of real datasets, you’ll delve into regression models through the use of a bike-sharing dataset, explore decision trees by leveraging New York City taxi data, and dissect parametric methods with baseball player stats. You’ll also find expert tips for avoiding common problems, like handling “dirty” or unbalanced data, and how to troubleshoot pitfalls. You’ll also explore: How to deal with large datasets and techniques for dimension reduction Details on how the Bias-Variance Trade-off plays out in specific ML methods Models based on linear relationships, including ridge and LASSO regression Real-world image and text classification and how to handle time series data Machine learning is an art that requires careful tuning and tweaking. With The Art of Machine Learning as your guide, you’ll master the underlying principles of ML that will empower you to effectively use these models, rather than simply provide a few stock actions with limited practical use. Requirements: A basic understanding of graphs and charts and familiarity with the R programming language
Book Synopsis Mike's Peanuts by : Rocket Baby Club
Download or read book Mike's Peanuts written by Rocket Baby Club and published by . This book was released on 2018-07-26 with total page 38 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning in artificial intelligence is finally accessible to kids! Mike the squirrel is digging peanuts to give as a present for his friend's birthday. Since peanuts grow underground, Mike needs to predict how deep he should dig. After a trip with Mike, you and your loved ones will know what linear regression is before you realize it!
Book Synopsis Art in the Age of Machine Learning by : Sofian Audry
Download or read book Art in the Age of Machine Learning written by Sofian Audry and published by MIT Press. This book was released on 2021-11-23 with total page 215 pages. Available in PDF, EPUB and Kindle. Book excerpt: An examination of machine learning art and its practice in new media art and music. Over the past decade, an artistic movement has emerged that draws on machine learning as both inspiration and medium. In this book, transdisciplinary artist-researcher Sofian Audry examines artistic practices at the intersection of machine learning and new media art, providing conceptual tools and historical perspectives for new media artists, musicians, composers, writers, curators, and theorists. Audry looks at works from a broad range of practices, including new media installation, robotic art, visual art, electronic music and sound, and electronic literature, connecting machine learning art to such earlier artistic practices as cybernetics art, artificial life art, and evolutionary art. Machine learning underlies computational systems that are biologically inspired, statistically driven, agent-based networked entities that program themselves. Audry explains the fundamental design of machine learning algorithmic structures in terms accessible to the nonspecialist while framing these technologies within larger historical and conceptual spaces. Audry debunks myths about machine learning art, including the ideas that machine learning can create art without artists and that machine learning will soon bring about superhuman intelligence and creativity. Audry considers learning procedures, describing how artists hijack the training process by playing with evaluative functions; discusses trainable machines and models, explaining how different types of machine learning systems enable different kinds of artistic practices; and reviews the role of data in machine learning art, showing how artists use data as a raw material to steer learning systems and arguing that machine learning allows for novel forms of algorithmic remixes.
Book Synopsis Python for Kids, 2nd Edition by : Jason R. Briggs
Download or read book Python for Kids, 2nd Edition written by Jason R. Briggs and published by No Starch Press. This book was released on 2022-11-15 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: The second edition of the best-selling Python for Kids—which brings you (and your parents) into the world of programming—has been completely updated to use the latest version of Python, along with tons of new projects! Python is a powerful programming language that’s easy to learn and fun to use! But books about programming in Python can be dull and that’s no fun for anyone. Python for Kids brings kids (and their parents) into the wonderful world of programming. Jason R. Briggs guides you through the basics, experimenting with unique (and hilarious) example programs featuring ravenous monsters, secret agents, thieving ravens, and more. New terms are defined; code is colored and explained; puzzles stretch the brain and strengthen understanding; and full-color illustrations keep you engaged throughout. By the end of the book, you’ll have programmed two games: a clone of the famous Pong, and “Mr. Stick Man Races for the Exit”—a platform game with jumps and animation. This second edition is revised and updated to reflect Python 3 programming practices. There are new puzzles to inspire you and two new appendices to guide you through Python’s built-in modules and troubleshooting your code. As you strike out on your programming adventure, you’ll learn how to: Use fundamental data structures like lists, tuples, and dictionaries Organize and reuse your code with functions and modules Use control structures like loops and conditional statements Draw shapes and patterns with Python’s turtle module Create games, animations, and other graphical wonders with tkinter Why should serious adults have all the fun? Python for Kids is your ticket into the amazing world of computer programming. Covers Python 3.x which runs on Windows, macOS, Linux, even Raspberry Pi
Book Synopsis Machine Learning - A Journey To Deep Learning: With Exercises And Answers by : Andreas Miroslaus Wichert
Download or read book Machine Learning - A Journey To Deep Learning: With Exercises And Answers written by Andreas Miroslaus Wichert and published by World Scientific. This book was released on 2021-01-26 with total page 641 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique compendium discusses some core ideas for the development and implementation of machine learning from three different perspectives — the statistical perspective, the artificial neural network perspective and the deep learning methodology.The useful reference text represents a solid foundation in machine learning and should prepare readers to apply and understand machine learning algorithms as well as to invent new machine learning methods. It tells a story outgoing from a perceptron to deep learning highlighted with concrete examples, including exercises and answers for the students.Related Link(s)
Book Synopsis Mathematics for Machine Learning by : Marc Peter Deisenroth
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.
Book Synopsis A Fresh Squeeze on Data - Problem Solving with Data by : ReadyAI
Download or read book A Fresh Squeeze on Data - Problem Solving with Data written by ReadyAI and published by . This book was released on 2021-07-23 with total page 57 pages. Available in PDF, EPUB and Kindle. Book excerpt: Is your child interested in solving big problems? Do they want to make the world a better place? What if they could do that through data? In A Fresh Squeeze on Data, Clara and Alex are two little kids with big ideas, all to help their local hospital. As their Lemonade Crew sets out to raise money by setting up a lemonade stand, they use data along their journey to understand factors like what to sell, where to set up their stand, as well as the role of bias in data. This fun and interactive book uses simple pictures, diagrams, and comprehensive terms to walk readers through the basics of data science, and also contains relevant activity sheets for kids to put data to work! Written by K-12 artificial intelligence education experts and popular children's authors ReadyAI in partnership with enterprise data cloud company Cloudera, the book is recommended for students ages 8 - 12 years old. "Hello Everyone, Thank you so much for reading this book! My sons, Flynn and Jedd, and I really enjoyed learning from Clara and Alex and hope you did too. In our world, it's very important that we understand where data comes from and how it can be used to make good predictions and decisions. Data can help us find the best solutions for people, our natural resources, and our communities. There are a lot of problems we can solve by analyzing data. The possibilities are limitless - just as they are for you! Thanks for starting early on your path to appreciating the value of data and developing your data literacy. You're on your way - keep it going!" - Scott Aronson, Proud father of two young boys & Chief Operating Officer at Cloudera
Book Synopsis The Children's Machine by : Seymour Papert
Download or read book The Children's Machine written by Seymour Papert and published by Basic Books. This book was released on 1994-04-29 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: In his classsic book, Mindstorms: Children, Computers, and powerful Ideas, Seymour Papert set out a vision of how computers could change school. In The Children's Machine he now looks back over a decade during which American schools acquired more than three million computers and assesses progress and resistance to progress.
Book Synopsis Machine Learning for Kids by : Dale Lane
Download or read book Machine Learning for Kids written by Dale Lane and published by . This book was released on 2021 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence (AI) is the ability of computers to simulate human thinking. Machine learning (ML) is one of the building blocks of AI. It's based on the idea that computers can be taught to do things on their own from the data and feedback you give them. Machine Learning for Kids consists of this book and a kid-friendly companion website paired with the educational coding platform, Scratch. Together, they provide an easy-to-use guided programming environment for adding ML capabilities to your own AI projects! As you work through each chapter you'll discover how ML systems can be taught to recognize text, images, numbers, and sounds, and different ways of training ML models to improve their accuracy. You'll turn your models into fun computer games and apps (and see what happens when an AI system gets confused by bad data) while building: •A Rock, Paper, Scissors game that knows your hand shapes •A smart question-answering chatbot •A computer character that reacts to insults and compliments •An interactive virtual assistant (like Amazon's Alexa) that obeys commands •An AI version of Pac-Man, with a character trained to avoid ghosts Requirements: No experience in machine learning or basic coding is necessary! This book includes a Scratch tutorial for beginners, and step-by-step instructions for every project.
Book Synopsis Neural Networks for Kids (Tinker Toddlers) by : Dhoot
Download or read book Neural Networks for Kids (Tinker Toddlers) written by Dhoot and published by . This book was released on 2019-02-08 with total page 28 pages. Available in PDF, EPUB and Kindle. Book excerpt: Simple explanations about emerging STEM (science, technology, engineering and mathematics) kick-starting your future genius! Neural Networks for Kids is a vibrant book exploring the very basics of neural networks, a web of smart cells that help you and machines learn, with a fun little story about Jaya's quest to collect flowers. This book will help familiarize your little one with how neurons look and function, both in us and in computing systems. The colorful, beautiful, and visually stimulating illustrations and two levels of learning encourage the child's sense of wonder, adventure, and curiosity (and might stimulate your senses too)! Levels of learning: Level 1 baby basics in black text and Level 2 in purple text for toddlers to build on. Look for other books by Tinker Toddlers: Machine Learning for Babies & Toddlers Artificial Intelligence for Babies & Toddlers ABCs of Machine Learning Solar System for Babies & Toddlers
Download or read book Simple Machines written by David A. Adler and published by National Geographic Books. This book was released on 2015-02-01 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: How many simple machines do you use every day? Probably more than you realize! Machines make work easier— helping break things apart, lift heavy objects, and change the power and direction of force applied to them. In this accessible picture book, celebrated nonfiction author David A. Adler outlines different types of simple machines—wedges, wheels, levers, pulleys, and more—and gives common examples of how we use them every day. Anna Raff's bright illustrations show how simple machines work—and add a dose of fun and humor, too. Two appealing kids and their comical cat use machines to ride see-saws, turn knobs, and even eat apples. Perfect for classrooms or for budding engineers to read on their own, Simple Machines uses clear, simple language to introduce important mechanical vocabulary, and easy-to-understand examples to illustrate how we use machines to solve all kinds of problems. Don't miss David A. Adler and Anna Raff's other science collaborations—including Light Waves; Magnets Push, Magnets Pull; and Things That Float and Things That Don't.
