My First Ai Book Artificial Intelligence And Learning

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MY FIRST A.I. BOOK - Artificial Intelligence and Learning

Author : Nicky Roberts
Publisher : My First A.I. Book
ISBN 13 : 9781513654249
Total Pages : 34 pages
Book Rating : 4.6/5 (542 download)

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Book Synopsis MY FIRST A.I. BOOK - Artificial Intelligence and Learning by : Nicky Roberts

Download or read book MY FIRST A.I. BOOK - Artificial Intelligence and Learning written by Nicky Roberts and published by My First A.I. Book. This book was released on 2019-08-30 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence and Learning is a teaser in a series of books and pioneering book for kids on Artificial Intelligence (A.I.) which focuses on its chief concept: LEARNING. The My First A.I. Books Series introduces kids of all ages to the foundational concepts for Artificial Intelligence and the 4th Industrial/Human Revolution, AKA I4.0 or 4IR or IOT. Written by three global experts and active scientific researchers, Professors Fernando Buarque (Ph.D. in A.I. Imperial College London), Tshilidzi Marwala (Ph.D. in A.I. at University of Cambridge), and Nicky Roberts (Ph.D. in Mathematics Education at the University of Witwatersrand).This book and series are suitable for all kids starting their Artificial Intelligence journey. As a matter of fact, the future of humankind depends centrally on how A.I. will be produced and used. As such, little readers are encouraged to think and talk in an informed manner about A.I. topics. The story of this first book, sets the plot by delving into the evolution of human tools (up to the fourth human revolution), types of learning, the ingredients for adaptive computer programs (i.e. programs that are able to learn), and even provides a working definition of A.I. All the books of the series are packed with concepts and encourage inquiry. They aim to widen the kids' perspectives on, and also nurture their participation with, these new concepts and tools. All that in this amazing unfolding revolution - the Revolution of the Intelligence. The authors took care to include not only technical concepts, but humanistic and character-building values too. Thus, readers would acquire a good foundation for their future, which may even not be a technical one (but certainly will include A.I.). Ideally, this book should be read by the kids with an adult. It is handsomely complemented by five more books, which portrait five missions, detailing other chief functional A.I. concepts. In each mission the explorers are challenged to delve (and learn) five different ways of using A.I. on real-world problems. The other books in the My First A.I. Books Series are: -My First A.I. Book - Mission of Team-B is Searching -My First A.I. Book - Mission of Team-R is Predicting-My First A.I. Book - Mission of Team-I is Classifying-My First A.I. Book - Mission of Team-C is Optimizing-My First A.I. Book - Mission of Team-S is Interfacing

The Essence of Artificial Intelligence

Author : Alison Cawsey
Publisher : Pearson
ISBN 13 : 9780135717790
Total Pages : 204 pages
Book Rating : 4.7/5 (177 download)

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Book Synopsis The Essence of Artificial Intelligence by : Alison Cawsey

Download or read book The Essence of Artificial Intelligence written by Alison Cawsey and published by Pearson. This book was released on 1998 with total page 204 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise, practical introduction to artificial intelligence, this title starts with the fundamentals of knowledge representation, inference, expert systems, natural language processing, machine learning, neural networks, agents, robots, and much more. Examples and algorithms are presented throughout, and the book includes a complete glossary.

Machine Learning with Python

Author : Abhishek Vijayvargia
Publisher : BPB Publications
ISBN 13 : 9789386551931
Total Pages : 268 pages
Book Rating : 4.5/5 (519 download)

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Book Synopsis Machine Learning with Python by : Abhishek Vijayvargia

Download or read book Machine Learning with Python written by Abhishek Vijayvargia and published by BPB Publications. This book was released on 2018-03-01 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing code examples in python, this book introduces the concepts of machine learning with mathematical explanations and programming fundamentals. --

AI and Machine Learning for Coders

Author : Laurence Moroney
Publisher : O'Reilly Media
ISBN 13 : 1492078166
Total Pages : 393 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis AI and Machine Learning for Coders by : Laurence Moroney

Download or read book AI and Machine Learning for Coders written by Laurence Moroney and published by O'Reilly Media. This book was released on 2020-10-01 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you're looking to make a career move from programmer to AI specialist, this is the ideal place to start. Based on Laurence Moroney's extremely successful AI courses, this introductory book provides a hands-on, code-first approach to help you build confidence while you learn key topics. You'll understand how to implement the most common scenarios in machine learning, such as computer vision, natural language processing (NLP), and sequence modeling for web, mobile, cloud, and embedded runtimes. Most books on machine learning begin with a daunting amount of advanced math. This guide is built on practical lessons that let you work directly with the code. You'll learn: How to build models with TensorFlow using skills that employers desire The basics of machine learning by working with code samples How to implement computer vision, including feature detection in images How to use NLP to tokenize and sequence words and sentences Methods for embedding models in Android and iOS How to serve models over the web and in the cloud with TensorFlow Serving

The AI-First Company

Author : Ash Fontana
Publisher : Penguin
ISBN 13 : 0593330315
Total Pages : 306 pages
Book Rating : 4.5/5 (933 download)

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Book Synopsis The AI-First Company by : Ash Fontana

Download or read book The AI-First Company written by Ash Fontana and published by Penguin. This book was released on 2021-05-04 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence is transforming every industry, but if you want to win with AI, you have to put it first on your priority list. AI-First companies are the only trillion-dollar companies, and soon they will dominate even more industries, more definitively than ever before. These companies succeed by design--they collect valuable data from day one and use it to train predictive models that automate core functions. As a result, they learn faster and outpace the competition in the process. Thankfully, you don't need a Ph.D. to learn how to win with AI. In The AI-First Company, internationally-renowned startup investor Ash Fontana offers an executable guide for applying AI to business problems. It's a playbook made for real companies, with real budgets, that need strategies and tactics to effectively implement AI. Whether you're a new online retailer or a Fortune 500 company, Fontana will teach you how to: • Identify the most valuable data; • Build the teams that build AI; • Integrate AI with existing processes and keep it in check; • Measure and communicate its effectiveness; • Reinvest the profits from automation to compound competitive advantage. If the last fifty years were about getting AI to work in the lab, the next fifty years will be about getting AI to work for people, businesses, and society. It's not about building the right software -- it's about building the right AI. The AI-First Company is your guide to winning with artificial intelligence.

Machine Learning: How Artificial Intelligence Learns (Fun Picture Book for K-2, AI+ME Series, Big Idea 3)

Author : ReadyAI
Publisher : Ready AI LLC
ISBN 13 :
Total Pages : 46 pages
Book Rating : 4./5 ( download)

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Book Synopsis Machine Learning: How Artificial Intelligence Learns (Fun Picture Book for K-2, AI+ME Series, Big Idea 3) by : ReadyAI

Download or read book Machine Learning: How Artificial Intelligence Learns (Fun Picture Book for K-2, AI+ME Series, Big Idea 3) written by ReadyAI and published by Ready AI LLC. This book was released on 2020-10-19 with total page 46 pages. Available in PDF, EPUB and Kindle. Book excerpt: Is your child interested in sci-fi, robots, or video games? Is your kid fascinated by smart home assistants and the prospect of self-driving cars? Time to turn that enthusiasm into action and engage with the exciting world of artificial intelligence! AI+Me is a series designed to introduce the 5 Big Ideas of Artificial Intelligence to young learners. Students take a deep dive into the Five Big Ideas of AI (Perception, Representation and Reasoning, Learning, Natural Interaction, and Societal Impact). This is the 3rd book in the AI+Me series focused on Learning. The series is recommended for K-2 students. Why should children be educated about AI? Learning AI opens up a world of opportunities. As the fastest growing area of computer science, AI will become the most important change force when our children grow up so it is critical they learn about it early. AI is fun! The field of AI started with scientists making computers learn to play games. AI is an incredibly fun way to introduce kids to programming and pique their interest in advanced topics like deep learning. Lastly, a topic like AI naturally opens up discussions about our humanity. In our curriculum, we dig deep into questions like “does AI positively or negatively impact society?” In doing so we aim to develop critical thinking skills and encourage students to reflect deeply. Benefits of AI education: - Gets children interested in #STEM education - Improves their problem-solving and critical-thinking skills - Builds their understanding of the tech tools that’ll shape their future - Starts important conversations about the future of humanity What are educators saying: “I really love these books. I think they are absolutely beautiful and very visually engaging ways for students to learn about artificial intelligence. I like how they progress through the topic and terms related to artificial intelligence and help students to attach meaning to what they are learning by the different examples and step-by-step ways that students build their understanding through the book.” - Rachelle Dene Poth, Author of In Other Words, Unconventional, The Future is Now, and Chart a New Course. What are parents saying: “My 1st grader loves this book. She already is really interested in computers, but this book got her thinking about how we actually tell emotions. She started using her camera on her computer to record different expressions.” “My son learned ReadyAI courses before. I let his friend read AI+Me big idea 1. Surprisingly, both of them finished reading the book, with a lot of interest! I Will recommend this book for elementary school students.” “I have been looking for fun ways to introduce AI to my kid, and this definitely nailed it.”

A First Course in Artificial Intelligence

Author : Osondu Oguike
Publisher : Bentham Science Publishers
ISBN 13 : 1681088541
Total Pages : 343 pages
Book Rating : 4.6/5 (81 download)

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Book Synopsis A First Course in Artificial Intelligence by : Osondu Oguike

Download or read book A First Course in Artificial Intelligence written by Osondu Oguike and published by Bentham Science Publishers. This book was released on 2021-07-14 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: The importance of Artificial Intelligence cannot be over-emphasised in current times, where automation is already an integral part of industrial and business processes. A First Course in Artificial Intelligence is a comprehensive textbook for beginners which covers all the fundamentals of Artificial Intelligence. Seven chapters (divided into thirty-three units) introduce the student to key concepts of the discipline in simple language, including expert system, natural language processing, machine learning, machine learning applications, sensory perceptions (computer vision, tactile perception) and robotics. Each chapter provides information in separate units about relevant history, applications, algorithm and programming with relevant case studies and examples. The simplified approach to the subject enables beginners in computer science who have a basic knowledge of Java programming to easily understand the contents. The text also introduces Python programming language basics, with demonstrations of natural language processing. It also introduces readers to the Waikato Environment for Knowledge Analysis (WEKA), as a tool for machine learning. The book is suitable for students and teachers involved in introductory courses in undergraduate and diploma level courses which have appropriate modules on artificial intelligence.

The AI-Powered Enterprise

Author : Seth Earley
Publisher : LifeTree Media
ISBN 13 : 1928055524
Total Pages : 203 pages
Book Rating : 4.9/5 (28 download)

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Book Synopsis The AI-Powered Enterprise by : Seth Earley

Download or read book The AI-Powered Enterprise written by Seth Earley and published by LifeTree Media. This book was released on 2020-04-28 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.

Perception: How Artificial Intelligence Sees the World (Fun Picture Book for K-2, AI+ME Series)

Author : ReadyAI
Publisher : Ready AI LLC
ISBN 13 :
Total Pages : 43 pages
Book Rating : 4./5 ( download)

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Book Synopsis Perception: How Artificial Intelligence Sees the World (Fun Picture Book for K-2, AI+ME Series) by : ReadyAI

Download or read book Perception: How Artificial Intelligence Sees the World (Fun Picture Book for K-2, AI+ME Series) written by ReadyAI and published by Ready AI LLC. This book was released on 2020-09-30 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: Is your child interested in sci-fi, robots, or video games? Is your kid fascinated by smart home assistants and the prospect of self-driving cars? Time to turn that enthusiasm into action and engage with the exciting world of artificial intelligence! AI+Me is a series designed to introduce the 5 Big Ideas of Artificial Intelligence to young learners. Students take a deep dive into the Five Big Ideas of AI (Perception, Representation and Reasoning, Learning, Natural Interaction, and Societal Impact). This is the first book in the AI+Me series focused on Perception. The series is recommended for K-2 students. Why should children be educated about AI? Learning AI opens up a world of opportunities. As the fastest growing area of computer science, AI will become the most important change force when our children grow up so it is critical they learn about it early. AI is fun! The field of AI started with scientists making computers learn to play games. AI is an incredibly fun way to introduce kids to programming and pique their interest in advanced topics like deep learning. Lastly, a topic like AI naturally opens up discussions about our humanity. In our curriculum, we dig deep into questions like “does AI positively or negatively impact society?” In doing so we aim to develop critical thinking skills and encourage students to reflect deeply. Benefits of AI education: - Gets children interested in #STEM education - Improves their problem-solving and critical-thinking skills - Builds their understanding of the tech tools that’ll shape their future - Starts important conversations about the future of humanity What are educators saying: “I really love these books. I think they are absolutely beautiful and very visually engaging ways for students to learn about artificial intelligence. I like how they progress through the topic and terms related to artificial intelligence and help students to attach meaning to what they are learning by the different examples and step-by-step ways that students build their understanding through the book.” - Rachelle Dene Poth, Author of In Other Words, Unconventional, The Future is Now, and Chart a New Course. What are parents saying: “My 1st grader loves this book. She already is really interested in computers, but this book got her thinking about how we actually tell emotions. She started using her camera on her computer to record different expressions.” “My son learned ReadyAI courses before. I let his friend read AI+Me big idea 1. Surprisingly, both of them finished reading the book, with a lot of interest! I Will recommend this book for elementary school students.” “I have been looking for fun ways to introduce AI to my kid, and this definitely nailed it.”

Introduction to Artificial Intelligence

Author : Wolfgang Ertel
Publisher : Springer
ISBN 13 : 3319584871
Total Pages : 365 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Introduction to Artificial Intelligence by : Wolfgang Ertel

Download or read book Introduction to Artificial Intelligence written by Wolfgang Ertel and published by Springer. This book was released on 2018-01-18 with total page 365 pages. Available in PDF, EPUB and Kindle. Book excerpt: This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning. Topics and features: presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and solutions, highlighted examples, definitions, theorems, and illustrative cartoons; includes chapters on predicate logic, PROLOG, heuristic search, probabilistic reasoning, machine learning and data mining, neural networks and reinforcement learning; reports on developments in deep learning, including applications of neural networks to generate creative content such as text, music and art (NEW); examines performance evaluation of clustering algorithms, and presents two practical examples explaining Bayes’ theorem and its relevance in everyday life (NEW); discusses search algorithms, analyzing the cycle check, explaining route planning for car navigation systems, and introducing Monte Carlo Tree Search (NEW); includes a section in the introduction on AI and society, discussing the implications of AI on topics such as employment and transportation (NEW). Ideal for foundation courses or modules on AI, this easy-to-read textbook offers an excellent overview of the field for students of computer science and other technical disciplines, requiring no more than a high-school level of knowledge of mathematics to understand the material.

Artificial Intelligence and TheFuture of Power

Author : Rajiv Malhotra
Publisher : Rupa Publications India Pvt Limited
ISBN 13 : 9789390356430
Total Pages : 522 pages
Book Rating : 4.3/5 (564 download)

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Book Synopsis Artificial Intelligence and TheFuture of Power by : Rajiv Malhotra

Download or read book Artificial Intelligence and TheFuture of Power written by Rajiv Malhotra and published by Rupa Publications India Pvt Limited. This book was released on 2021-01-10 with total page 522 pages. Available in PDF, EPUB and Kindle. Book excerpt: A recurrent debate surrounding AI concerns the extent of human work that could be replaced by machines over the next twenty years when compared to new jobs created by AI. Numerous reports have addressed this issue, reaching a wide range of conclusions. Experts consider it a reasonable consensus that eventually a significant portion of blue- and white-collar jobs in most industries will become obsolete, or at least transformed, to such an extent that workers will need re-education to remain viable. This percentage of vulnerable jobs will continue to increase over time. The obsolescence will be far worse in developing countries where the standard of education is lower.

Hands-On Deep Learning Algorithms with Python

Author : Sudharsan Ravichandiran
Publisher : Packt Publishing Ltd
ISBN 13 : 1789344514
Total Pages : 498 pages
Book Rating : 4.7/5 (893 download)

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Book Synopsis Hands-On Deep Learning Algorithms with Python by : Sudharsan Ravichandiran

Download or read book Hands-On Deep Learning Algorithms with Python written by Sudharsan Ravichandiran and published by Packt Publishing Ltd. This book was released on 2019-07-25 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand basic to advanced deep learning algorithms, the mathematical principles behind them, and their practical applications. Key FeaturesGet up-to-speed with building your own neural networks from scratch Gain insights into the mathematical principles behind deep learning algorithmsImplement popular deep learning algorithms such as CNNs, RNNs, and more using TensorFlowBook Description Deep learning is one of the most popular domains in the AI space, allowing you to develop multi-layered models of varying complexities. This book introduces you to popular deep learning algorithms—from basic to advanced—and shows you how to implement them from scratch using TensorFlow. Throughout the book, you will gain insights into each algorithm, the mathematical principles behind it, and how to implement it in the best possible manner. The book starts by explaining how you can build your own neural networks, followed by introducing you to TensorFlow, the powerful Python-based library for machine learning and deep learning. Moving on, you will get up to speed with gradient descent variants, such as NAG, AMSGrad, AdaDelta, Adam, and Nadam. The book will then provide you with insights into RNNs and LSTM and how to generate song lyrics with RNN. Next, you will master the math for convolutional and capsule networks, widely used for image recognition tasks. Then you learn how machines understand the semantics of words and documents using CBOW, skip-gram, and PV-DM. Afterward, you will explore various GANs, including InfoGAN and LSGAN, and autoencoders, such as contractive autoencoders and VAE. By the end of this book, you will be equipped with all the skills you need to implement deep learning in your own projects. What you will learnImplement basic-to-advanced deep learning algorithmsMaster the mathematics behind deep learning algorithmsBecome familiar with gradient descent and its variants, such as AMSGrad, AdaDelta, Adam, and NadamImplement recurrent networks, such as RNN, LSTM, GRU, and seq2seq modelsUnderstand how machines interpret images using CNN and capsule networksImplement different types of generative adversarial network, such as CGAN, CycleGAN, and StackGANExplore various types of autoencoder, such as Sparse autoencoders, DAE, CAE, and VAEWho this book is for If you are a machine learning engineer, data scientist, AI developer, or simply want to focus on neural networks and deep learning, this book is for you. Those who are completely new to deep learning, but have some experience in machine learning and Python programming, will also find the book very helpful.

Artificial Intelligence

Author : Jerry Kaplan
Publisher : Oxford University Press
ISBN 13 : 0190602406
Total Pages : 193 pages
Book Rating : 4.1/5 (96 download)

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Book Synopsis Artificial Intelligence by : Jerry Kaplan

Download or read book Artificial Intelligence written by Jerry Kaplan and published by Oxford University Press. This book was released on 2016-09-01 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the coming decades, Artificial Intelligence will profoundly impact the way we live, work, wage war, play, seek a mate, educate our young, and care for our elderly. It is likely to greatly increase our aggregate wealth, but it will also upend our labor markets, reshuffle our social order, and strain our private and public institutions. Eventually it may alter how we see our place in the universe, as machines pursue goals independent of their creators and outperform us in domains previously believed to be the sole dominion of humans. Whether we regard them as conscious or unwitting, revere them as a new form of life or dismiss them as mere clever appliances, is beside the point. They are likely to play an increasingly critical and intimate role in many aspects of our lives. The emergence of systems capable of independent reasoning and action raises serious questions about just whose interests they are permitted to serve, and what limits our society should place on their creation and use. Deep ethical questions that have bedeviled philosophers for ages will suddenly arrive on the steps of our courthouses. Can a machine be held accountable for its actions? Should intelligent systems enjoy independent rights and responsibilities, or are they simple property? Who should be held responsible when a self-driving car kills a pedestrian? Can your personal robot hold your place in line, or be compelled to testify against you? If it turns out to be possible to upload your mind into a machine, is that still you? The answers may surprise you.

Contemporary Artificial Intelligence

Author : Richard E. Neapolitan
Publisher : CRC Press
ISBN 13 : 1439844690
Total Pages : 517 pages
Book Rating : 4.4/5 (398 download)

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Book Synopsis Contemporary Artificial Intelligence by : Richard E. Neapolitan

Download or read book Contemporary Artificial Intelligence written by Richard E. Neapolitan and published by CRC Press. This book was released on 2012-08-25 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: The notion of artificial intelligence (AI) often sparks thoughts of characters from science fiction, such as the Terminator and HAL 9000. While these two artificial entities do not exist, the algorithms of AI have been able to address many real issues, from performing medical diagnoses to navigating difficult terrain to monitoring possible failures of spacecrafts. Exploring these algorithms and applications, Contemporary Artificial Intelligence presents strong AI methods and algorithms for solving challenging problems involving systems that behave intelligently in specialized domains such as medical and software diagnostics, financial decision making, speech and text recognition, genetic analysis, and more. One of the first AI texts accessible to students, the book focuses on the most useful problem-solving strategies that have emerged from AI. In a student-friendly way, the authors cover logic-based methods; probability-based methods; emergent intelligence, including evolutionary computation and swarm intelligence; data-derived logical and probabilistic learning models; and natural language understanding. Through reading this book, students discover the importance of AI techniques in computer science.

Machine Learning

Author : Ethem Alpaydin
Publisher : MIT Press
ISBN 13 : 0262529513
Total Pages : 225 pages
Book Rating : 4.2/5 (625 download)

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Book Synopsis Machine Learning by : Ethem Alpaydin

Download or read book Machine Learning written by Ethem Alpaydin and published by MIT Press. This book was released on 2016-10-07 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise overview of machine learning—computer programs that learn from data—which underlies applications that include recommendation systems, face recognition, and driverless cars. Today, machine learning underlies a range of applications we use every day, from product recommendations to voice recognition—as well as some we don't yet use everyday, including driverless cars. It is the basis of the new approach in computing where we do not write programs but collect data; the idea is to learn the algorithms for the tasks automatically from data. As computing devices grow more ubiquitous, a larger part of our lives and work is recorded digitally, and as “Big Data” has gotten bigger, the theory of machine learning—the foundation of efforts to process that data into knowledge—has also advanced. In this book, machine learning expert Ethem Alpaydin offers a concise overview of the subject for the general reader, describing its evolution, explaining important learning algorithms, and presenting example applications. Alpaydin offers an account of how digital technology advanced from number-crunching mainframes to mobile devices, putting today's machine learning boom in context. He describes the basics of machine learning and some applications; the use of machine learning algorithms for pattern recognition; artificial neural networks inspired by the human brain; algorithms that learn associations between instances, with such applications as customer segmentation and learning recommendations; and reinforcement learning, when an autonomous agent learns act so as to maximize reward and minimize penalty. Alpaydin then considers some future directions for machine learning and the new field of “data science,” and discusses the ethical and legal implications for data privacy and security.

Python Artificial Intelligence Projects for Beginners

Author : Dr. Joshua Eckroth
Publisher : Packt Publishing Ltd
ISBN 13 : 1789538246
Total Pages : 155 pages
Book Rating : 4.7/5 (895 download)

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Book Synopsis Python Artificial Intelligence Projects for Beginners by : Dr. Joshua Eckroth

Download or read book Python Artificial Intelligence Projects for Beginners written by Dr. Joshua Eckroth and published by Packt Publishing Ltd. This book was released on 2018-07-31 with total page 155 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build smart applications by implementing real-world artificial intelligence projects Key Features Explore a variety of AI projects with Python Get well-versed with different types of neural networks and popular deep learning algorithms Leverage popular Python deep learning libraries for your AI projects Book Description Artificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence. This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library. By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress What you will learn Build a prediction model using decision trees and random forest Use neural networks, decision trees, and random forests for classification Detect YouTube comment spam with a bag-of-words and random forests Identify handwritten mathematical symbols with convolutional neural networks Revise the bird species identifier to use images Learn to detect positive and negative sentiment in user reviews Who this book is for Python Artificial Intelligence Projects for Beginners is for Python developers who want to take their first step into the world of Artificial Intelligence using easy-to-follow projects. Basic working knowledge of Python programming is expected so that you’re able to play around with code

Mathematics for Machine Learning

Author : Marc Peter Deisenroth
Publisher : Cambridge University Press
ISBN 13 : 1108569323
Total Pages : 392 pages
Book Rating : 4.1/5 (85 download)

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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.