Generative Ai Explained Your Essential Guide

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Generative AI Explained: Your Essential Guide

Author : Anand Vemula
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 23 pages
Book Rating : 4./5 ( download)

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Book Synopsis Generative AI Explained: Your Essential Guide by : Anand Vemula

Download or read book Generative AI Explained: Your Essential Guide written by Anand Vemula and published by Anand Vemula. This book was released on with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Generative AI Explained: Your Essential Guide" offers a clear and concise introduction to the world of generative artificial intelligence (AI). Authored by experts in the field, this handbook provides readers with a comprehensive understanding of the principles, applications, and implications of generative AI technology. The book begins by demystifying the concept of generative AI, explaining how it differs from other forms of AI and detailing its underlying mechanisms. Readers are guided through key concepts such as neural networks, machine learning, and deep learning, gaining insights into how these technologies enable machines to generate new content autonomously. From there, the handbook delves into practical applications of generative AI across various industries. Through real-world examples and case studies, readers discover how generative AI is being used to create art, music, literature, and even video games. Additionally, the book explores its applications in fields like healthcare, finance, and marketing, highlighting the transformative impact it is having on society. Furthermore, the handbook addresses important ethical and societal considerations surrounding generative AI. Readers are encouraged to critically examine issues such as bias, privacy, and the implications of AI-generated content on human creativity and employment. Throughout the book, complex technical concepts are explained in a clear and accessible manner, making it suitable for readers with varying levels of technical expertise. Whether you're a student, researcher, developer, or simply curious about the future of AI, "Generative AI Explained" serves as an invaluable resource for understanding the fundamentals of this rapidly evolving field. In summary, "Generative AI Explained: Your Essential Guide" offers a comprehensive yet approachable exploration of generative artificial intelligence, equipping readers with the knowledge and insights needed to navigate the increasingly AI-driven world.

Generative Deep Learning

Author : David Foster
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492041890
Total Pages : 301 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Generative Deep Learning by : David Foster

Download or read book Generative Deep Learning written by David Foster and published by "O'Reilly Media, Inc.". This book was released on 2019-06-28 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

The Executive Guide to Artificial Intelligence

Author : Andrew Burgess
Publisher : Springer
ISBN 13 : 3319638203
Total Pages : 187 pages
Book Rating : 4.3/5 (196 download)

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Book Synopsis The Executive Guide to Artificial Intelligence by : Andrew Burgess

Download or read book The Executive Guide to Artificial Intelligence written by Andrew Burgess and published by Springer. This book was released on 2017-11-15 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book takes a pragmatic and hype–free approach to explaining artificial intelligence and how it can be utilised by businesses today. At the core of the book is a framework, developed by the author, which describes in non–technical language the eight core capabilities of Artificial Intelligence (AI). Each of these capabilities, ranging from image recognition, through natural language processing, to prediction, is explained using real–life examples and how they can be applied in a business environment. It will include interviews with executives who have successfully implemented AI as well as CEOs from AI vendors and consultancies. AI is one of the most talked about technologies in business today. It has the ability to deliver step–change benefits to organisations and enables forward–thinking CEOs to rethink their business models or create completely new businesses. But most of the real value of AI is hidden behind marketing hyperbole, confusing terminology, inflated expectations and dire warnings of ‘robot overlords’. Any business executive that wants to know how to exploit AI in their business today is left confused and frustrated. As an advisor in Artificial Intelligence, Andrew Burgess regularly comes face–to–face with business executives who are struggling to cut through the hype that surrounds AI. The knowledge and experience he has gained in advising them, as well as working as a strategic advisor to AI vendors and consultancies, has provided him with the skills to help business executives understand what AI is and how they can exploit its many benefits. Through the distilled knowledge included in this book business leaders will be able to take full advantage of this most disruptive of technologies and create substantial competitive advantage for their companies.

A Citizen's Guide to Artificial Intelligence

Author : John Zerilli
Publisher : MIT Press
ISBN 13 : 0262044811
Total Pages : 233 pages
Book Rating : 4.2/5 (62 download)

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Book Synopsis A Citizen's Guide to Artificial Intelligence by : John Zerilli

Download or read book A Citizen's Guide to Artificial Intelligence written by John Zerilli and published by MIT Press. This book was released on 2021-02-23 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: A concise but informative overview of AI ethics and policy. Artificial intelligence, or AI for short, has generated a staggering amount of hype in the past several years. Is it the game-changer it's been cracked up to be? If so, how is it changing the game? How is it likely to affect us as customers, tenants, aspiring home-owners, students, educators, patients, clients, prison inmates, members of ethnic and sexual minorities, voters in liberal democracies? This book offers a concise overview of moral, political, legal and economic implications of AI. It covers the basics of AI's latest permutation, machine learning, and considers issues including transparency, bias, liability, privacy, and regulation.

Artificial Intelligence Simplified

Author : Binto George
Publisher : CSTrends LLP
ISBN 13 : 1944708022
Total Pages : 1 pages
Book Rating : 4.9/5 (447 download)

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Book Synopsis Artificial Intelligence Simplified by : Binto George

Download or read book Artificial Intelligence Simplified written by Binto George and published by CSTrends LLP. This book was released on 2016-01-08 with total page 1 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book introduces key Artificial Intelligence (AI) concepts in an easy-to-read format with examples and illustrations. A complex, long, overly mathematical textbook does not always serve the purpose of conveying the basic AI concepts to most people. Someone with basic knowledge in Computer Science can have a quick overview of AI (heuristic searches, genetic algorithms, expert systems, game trees, fuzzy expert systems, natural language processing, super intelligence, etc.) with everyday examples. If you are taking a basic AI course and find the traditional AI textbooks intimidating, you may choose this as a “bridge” book, or as an introductory textbook. For students, there is a lower priced edition (ISBN 978-1944708016) of the same book. Published by CSTrends LLP.

Ultimate Step by Step Guide to Deep Learning Using Python

Author : Daneyal Anis
Publisher :
ISBN 13 :
Total Pages : 200 pages
Book Rating : 4.6/5 (658 download)

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Book Synopsis Ultimate Step by Step Guide to Deep Learning Using Python by : Daneyal Anis

Download or read book Ultimate Step by Step Guide to Deep Learning Using Python written by Daneyal Anis and published by . This book was released on 2020-07-19 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: *Start your Data Science career using Python today!*Are you ready to start your new exciting career? Ready to master artificial intelligence and deep learning concepts?Are you overwhelmed with complexity of the books on this subject?Then let this breezy and fun little book on Python, Machine Learning and Deep Learning models make you a Data Scientist in 7 days!This book continues from where the first book in the series, Ultimate Step by Step Guide to Machine Learning Using Python, left of. In the first book you were introduced to Python concepts such as: -Data Structures like Pandas -Foundational libraries like Numpy, Seaborn and Scikit-Learn-Regression analysis-Classification-Clustering-Association Learning-Dimension ReductionThis book builds on those concepts to expand on Machine Learning algorithms like: -Linear and Logistical regression-Decision tree-Support vector machines (SVM)After that, this book takes you on a journey into Deep Learning and Neural Networks with important concepts and libraries like: -Convolutional and Recurrent Neural Networks-TensorFlow-Keras-PyTorch-Keras-Apache MXNet-Microsoft Cognitive Toolkit (CNTK)The final part of the book covers all foundational concepts that are required for Amazon Web Services (AWS) Certified Machine Learning Specialization by explaining how to deploy your models at scale on Cloud technologies. While AWS is used in the book for illustrative purposes, Microsoft Azure and Google Cloud are also introduced as alternative cloud technologies. After reading this book you will be able to: -Code in Python with confidence-Build new machine learning and deep learning models from scratch-Know how to clean and prepare your data for analytics-Speak confidently about statistical analysis techniquesData Science was ranked the fast-growing field by LinkedIn and Data Scientist is one of the most highly sought after and lucrative careers in the world!If you are on the fence about making the leap to a new and lucrative career, this is the book for you!What sets this book apart from other books on the topic of Python and Machine learning: -Step by step code examples and explanation-Complex concepts explained visually-Real world applicability of the machine learning and deep learning models introducedWhat do I need to get started?You will have a step by step action plan in place once you finish this book and finally feel that you, can master data science and artificial intelligence and start a lucrative and rewarding career! Ready to dive in to the exciting world of Python and Deep Learning?Then scroll up to the top and hit that BUY BUTTON!

You Look Like a Thing and I Love You

Author : Janelle Shane
Publisher : Voracious
ISBN 13 : 0316525235
Total Pages : 272 pages
Book Rating : 4.3/5 (165 download)

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Book Synopsis You Look Like a Thing and I Love You by : Janelle Shane

Download or read book You Look Like a Thing and I Love You written by Janelle Shane and published by Voracious. This book was released on 2019-11-05 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: As heard on NPR's "Science Friday," discover the book recommended by Malcolm Gladwell, Susan Cain, Daniel Pink, and Adam Grant: an "accessible, informative, and hilarious" introduction to the weird and wonderful world of artificial intelligence (Ryan North). "You look like a thing and I love you" is one of the best pickup lines ever . . . according to an artificial intelligence trained by scientist Janelle Shane, creator of the popular blog AI Weirdness. She creates silly AIs that learn how to name paint colors, create the best recipes, and even flirt (badly) with humans—all to understand the technology that governs so much of our daily lives. We rely on AI every day for recommendations, for translations, and to put cat ears on our selfie videos. We also trust AI with matters of life and death, on the road and in our hospitals. But how smart is AI really... and how does it solve problems, understand humans, and even drive self-driving cars? Shane delivers the answers to every AI question you've ever asked, and some you definitely haven't. Like, how can a computer design the perfect sandwich? What does robot-generated Harry Potter fan-fiction look like? And is the world's best Halloween costume really "Vampire Hog Bride"? In this smart, often hilarious introduction to the most interesting science of our time, Shane shows how these programs learn, fail, and adapt—and how they reflect the best and worst of humanity. You Look Like a Thing and I Love You is the perfect book for anyone curious about what the robots in our lives are thinking. "I can't think of a better way to learn about artificial intelligence, and I've never had so much fun along the way." —Adam Grant, New York Times bestselling author of Originals

Ultimate Step by Step Guide to Machine Learning Using Python

Author : Daneyal Anis
Publisher :
ISBN 13 :
Total Pages : 68 pages
Book Rating : 4.6/5 (113 download)

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Book Synopsis Ultimate Step by Step Guide to Machine Learning Using Python by : Daneyal Anis

Download or read book Ultimate Step by Step Guide to Machine Learning Using Python written by Daneyal Anis and published by . This book was released on 2020-02-17 with total page 68 pages. Available in PDF, EPUB and Kindle. Book excerpt: *Start your Data Science career using Python today!* Are you ready to start your new exciting career? Ready to crush your machine learning career goals? Are you overwhelmed with complexity of the books on this subject?Then let this breezy and fun little book on Python and machine learning models make you a data scientist in 7 days! First part of this book introduces Python basics including: 1) Data Structures like Pandas 2) Foundational libraries like Numpy, Seaborn and Scikit-Learn Second part of this book shows you how to build predictive machine learning models step by step using techniques such as: 1) Regression analysis 2) Decision tree analysis 3) Training and testing data models 4) And much more! After reading this book you will be able to: 1) Code in Python with confidence 2) Build new machine learning models from scratch 3) Know how to clean and prepare your data for analytics 4) Speak confidently about statistical analysis techniques Data Science was ranked the fast-growing field by LinkedIn and Data Scientist is one of the most highly sought after and lucrative careers in the world! If you are on the fence about making the leap to a new and lucrative career, this is the book for you! What sets this book apart from other books on the topic of Python and Machine learning: 1) Step by step code examples and explanation 2) Complex concepts explained visually 3) Real world applicability of the machine learning models introduced 4) Bonus free code samples that you can try yourself without any prior experience in Python! What do I need to get started? You will have a step by step action plan in place once you finish this book and finally feel that you, can master data science and machine learning and start lucrative and rewarding career! Ready to dive in to the exciting world of Python and Machine Learning? Then scroll up to the top and hit that BUY BUTTON!

Artificial Intelligence For Dummies

Author : John Paul Mueller
Publisher : John Wiley & Sons
ISBN 13 : 1119467586
Total Pages : 60 pages
Book Rating : 4.1/5 (194 download)

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Book Synopsis Artificial Intelligence For Dummies by : John Paul Mueller

Download or read book Artificial Intelligence For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2018-03-16 with total page 60 pages. Available in PDF, EPUB and Kindle. Book excerpt: Step into the future with AI The term "Artificial Intelligence" has been around since the 1950s, but a lot has changed since then. Today, AI is referenced in the news, books, movies, and TV shows, and the exact definition is often misinterpreted. Artificial Intelligence For Dummies provides a clear introduction to AI and how it’s being used today. Inside, you’ll get a clear overview of the technology, the common misconceptions surrounding it, and a fascinating look at its applications in everything from self-driving cars and drones to its contributions in the medical field. Learn about what AI has contributed to society Explore uses for AI in computer applications Discover the limits of what AI can do Find out about the history of AI The world of AI is fascinating—and this hands-on guide makes it more accessible than ever!

Applied Artificial Intelligence

Author : Mariya Yao
Publisher :
ISBN 13 : 9780998289021
Total Pages : 246 pages
Book Rating : 4.2/5 (89 download)

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Book Synopsis Applied Artificial Intelligence by : Mariya Yao

Download or read book Applied Artificial Intelligence written by Mariya Yao and published by . This book was released on 2018-04-30 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This bestselling book gives business leaders and executives a foundational education on how to leverage artificial intelligence and machine learning solutions to deliver ROI for your business.

Machine Learning For Dummies

Author : John Paul Mueller
Publisher : John Wiley & Sons
ISBN 13 : 1119724015
Total Pages : 471 pages
Book Rating : 4.1/5 (197 download)

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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.

Understanding Michael Porter

Author : Joan Magretta
Publisher : Harvard Business Press
ISBN 13 : 1422160599
Total Pages : 250 pages
Book Rating : 4.4/5 (221 download)

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Book Synopsis Understanding Michael Porter by : Joan Magretta

Download or read book Understanding Michael Porter written by Joan Magretta and published by Harvard Business Press. This book was released on 2012 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to Michael Porters thinking on competition and strategy, classic and current.

Deep Learning Illustrated

Author : Jon Krohn
Publisher : Addison-Wesley Professional
ISBN 13 : 0135121728
Total Pages : 725 pages
Book Rating : 4.1/5 (351 download)

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Book Synopsis Deep Learning Illustrated by : Jon Krohn

Download or read book Deep Learning Illustrated written by Jon Krohn and published by Addison-Wesley Professional. This book was released on 2019-08-05 with total page 725 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The authors’ clear visual style provides a comprehensive look at what’s currently possible with artificial neural networks as well as a glimpse of the magic that’s to come." – Tim Urban, author of Wait But Why Fully Practical, Insightful Guide to Modern Deep Learning Deep learning is transforming software, facilitating powerful new artificial intelligence capabilities, and driving unprecedented algorithm performance. Deep Learning Illustrated is uniquely intuitive and offers a complete introduction to the discipline’s techniques. Packed with full-color figures and easy-to-follow code, it sweeps away the complexity of building deep learning models, making the subject approachable and fun to learn. World-class instructor and practitioner Jon Krohn–with visionary content from Grant Beyleveld and beautiful illustrations by Aglaé Bassens–presents straightforward analogies to explain what deep learning is, why it has become so popular, and how it relates to other machine learning approaches. Krohn has created a practical reference and tutorial for developers, data scientists, researchers, analysts, and students who want to start applying it. He illuminates theory with hands-on Python code in accompanying Jupyter notebooks. To help you progress quickly, he focuses on the versatile deep learning library Keras to nimbly construct efficient TensorFlow models; PyTorch, the leading alternative library, is also covered. You’ll gain a pragmatic understanding of all major deep learning approaches and their uses in applications ranging from machine vision and natural language processing to image generation and game-playing algorithms. Discover what makes deep learning systems unique, and the implications for practitioners Explore new tools that make deep learning models easier to build, use, and improve Master essential theory: artificial neurons, training, optimization, convolutional nets, recurrent nets, generative adversarial networks (GANs), deep reinforcement learning, and more Walk through building interactive deep learning applications, and move forward with your own artificial intelligence projects Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Artificial Intelligence Basics

Author : Tom Taulli
Publisher : Apress
ISBN 13 : 1484250281
Total Pages : 195 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Artificial Intelligence Basics by : Tom Taulli

Download or read book Artificial Intelligence Basics written by Tom Taulli and published by Apress. This book was released on 2019-08-01 with total page 195 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence touches nearly every part of your day. While you may initially assume that technology such as smart speakers and digital assistants are the extent of it, AI has in fact rapidly become a general-purpose technology, reverberating across industries including transportation, healthcare, financial services, and many more. In our modern era, an understanding of AI and its possibilities for your organization is essential for growth and success. Artificial Intelligence Basics has arrived to equip you with a fundamental, timely grasp of AI and its impact. Author Tom Taulli provides an engaging, non-technical introduction to important concepts such as machine learning, deep learning, natural language processing (NLP), robotics, and more. In addition to guiding you through real-world case studies and practical implementation steps, Taulli uses his expertise to expand on the bigger questions that surround AI. These include societal trends, ethics, and future impact AI will have on world governments, company structures, and daily life. Google, Amazon, Facebook, and similar tech giants are far from the only organizations on which artificial intelligence has had—and will continue to have—an incredibly significant result. AI is the present and the future of your business as well as your home life. Strengthening your prowess on the subject will prove invaluable to your preparation for the future of tech, and Artificial Intelligence Basics is the indispensable guide that you’ve been seeking. What You Will Learn Study the core principles for AI approaches such as machine learning, deep learning, and NLP (Natural Language Processing)Discover the best practices to successfully implement AI by examining case studies including Uber, Facebook, Waymo, UiPath, and Stitch FixUnderstand how AI capabilities for robots can improve businessDeploy chatbots and Robotic Processing Automation (RPA) to save costs and improve customer serviceAvoid costly gotchasRecognize ethical concerns and other risk factors of using artificial intelligenceExamine the secular trends and how they may impact your business Who This Book Is For Readers without a technical background, such as managers, looking to understand AI to evaluate solutions.

Deep Learning

Author : Ian Goodfellow
Publisher : MIT Press
ISBN 13 : 0262337371
Total Pages : 801 pages
Book Rating : 4.2/5 (623 download)

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Book Synopsis Deep Learning by : Ian Goodfellow

Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.

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

Humans Need Not Apply

Author : Jerry Kaplan
Publisher : Yale University Press
ISBN 13 : 0300216416
Total Pages : 256 pages
Book Rating : 4.3/5 (2 download)

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Book Synopsis Humans Need Not Apply by : Jerry Kaplan

Download or read book Humans Need Not Apply written by Jerry Kaplan and published by Yale University Press. This book was released on 2015-08-04 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: An “intriguing, insightful” look at how algorithms and robots could lead to social unrest—and how to avoid it (The Economist, Books of the Year). After decades of effort, researchers are finally cracking the code on artificial intelligence. Society stands on the cusp of unprecedented change, driven by advances in robotics, machine learning, and perception powering systems that rival or exceed human capabilities. Driverless cars, robotic helpers, and intelligent agents that promote our interests have the potential to usher in a new age of affluence and leisure—but as AI expert and Silicon Valley entrepreneur Jerry Kaplan warns, the transition may be protracted and brutal unless we address the two great scourges of the modern developed world: volatile labor markets and income inequality. In Humans Need Not Apply, he proposes innovative, free-market adjustments to our economic system and social policies to avoid an extended period of social turmoil. His timely and accessible analysis of the promises and perils of AI is a must-read for business leaders and policy makers on both sides of the aisle. “A reminder that AI systems don’t need red laser eyes to be dangerous.”—Times Higher Education Supplement “Kaplan…sidesteps the usual arguments of techno-optimism and dystopia, preferring to go for pragmatic solutions to a shrinking pool of jobs.”—Financial Times