The award-winning author Melanie Mitchell, a leading computer scientist, now reveals AI’s turbulent history and the recent spate of apparent successes, grand hopes, and emerging fears surrounding it.In Artificial Intelligence, Mitchell turns to the most urgent questions concerning AI today: How intelligent—really—are the best AI programs? How do they work? What can they actually do, and when do they fail? How humanlike do we expect them to become, and how soon do we need to worry about them surpassing us? Along the way, she introduces the dominant models of modern AI and machine learning, describing cutting-edge AI programs, their human inventors, and the historical lines of thought underpinning recent achievements. She meets with fellow experts such as Douglas Hofstadter, the cognitive scientist and Pulitzer Prize–winning author of the modern classic Gödel, Escher, Bach, who explains why he is “terrified” about the future of AI. She explores the profound disconnect between the hype and the actual achievements in AI, providing a clear sense of what the field has accomplished and how much further it has to go.Interweaving stories about the science of AI and the people behind it, Artificial Intelligence brims with clear-sighted, captivating, and accessible accounts of the most interesting and provocative modern work in the field, flavored with Mitchell’s humor and personal observations. This frank, lively book is an indispensable guide to understanding today’s AI, its quest for “human-level” intelligence, and its impact on the future for us all.

    During that week, you will learn almost everything modern machine learning has to offer. The author and other practitioners have spent years learning these concepts.Companion wiki — the book has a continuously updated wiki that extends some book chapters with additional information: Q&A, code snippets, further reading, tools, and other relevant resources.Flexible price and formats — choose from a variety of formats and price options: Kindle, hardcover, paperback, EPUB, PDF. If you buy an EPUB or a PDF, you decide the price you pay!Read first, buy later — download book chapters for free, read them and share with your friends and colleagues. Only if you liked the book or found it useful in your work, study or business, then buy it.

    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.

    SHOEMAKER. Shoemaker proves why he has consitently been praised as one of the best story writers in SF today with this touching, thoughtful, action-packed debut novel, based on his award-winning short story Today I am Paul.TODAY Mildred has Alzheimer's. As memories fade, she acquires the aid of a full-time android to assist her in everyday life. Carey. Carey takes care of Mildred, but its true mission is to fill in the gaps in Mildred’s past. To bring yesterday into today by becoming a copy. But not merely a copy of a physical person. A copy from the inside out. I AM After Mildred passes, Carey must find a new purpose. For a time, that purpose is Mildred’s family. To keep them safe from harm. To be of service. There is Paul Owens, the overworked scientist and business leader. Susan Owens, the dedicated teacher. And Millie, a curious little girl who will grow up alongside her android best friend. And Carey will grow up with her. Carey cannot age. But Carey can change. CAREY Carey struggles. Carey seeks to understand life’s challenges. Carey makes its own path. Carey must learn to live. To grow. To care. To survive. To be.Advance praise for Today I Am Carey:"Kindness, love, and compassion make Carey an empathetic character through which to view Shoemaker's complex, beautiful world."—Publishers Weekly"Martin Shoemaker proves conclusively that while a science fiction novel must have the trappings of science fiction, it is at its strongest when it is about people, even an artificial (but emotional) person named Carey."—Mike Resnick “A dazzling ride through the near future. I enjoyed it thoroughly. I’ve never seen anything remotely like it.”—Jack McDevitt “Martin Shoemaker is a rare writer who can handle the challenges of dealing with future technology while touching the human heart. This is a must-read!"—David Farland, New York Times Best-selling Author  Praise for the work of Martin L. Shoemaker: "Martin Shoemaker’s ‘Black Orbit’ is a more conventional Analog adventure, and a very good example of such . . . a really solid story." — Rich Horton, Locus Online "['Bookmark'] is an exceptional example of how to discuss deep moral and philosophical issues while maintaining a tight narrative that brings the reader along. This story will be added to the required readings for my SF classes. – Robert L Turner III, Tangent Online

    Conflict between humans and machines is seen as inevitable and its outcome all too predictable.In this groundbreaking book, distinguished AI researcher Stuart Russell argues that this scenario can be avoided, but only if we rethink AI from the ground up. Russell begins by exploring the idea of intelligence in humans and in machines. He describes the near-term benefits we can expect, from intelligent personal assistants to vastly accelerated scientific research, and outlines the AI breakthroughs that still have to happen before we reach superhuman AI. He also spells out the ways humans are already finding to misuse AI, from lethal autonomous weapons to viral sabotage.If the predicted breakthroughs occur and superhuman AI emerges, we will have created entities far more powerful than ourselves. How can we ensure they never, ever, have power over us? Russell suggests that we can rebuild AI on a new foundation, according to which machines are designed to be inherently uncertain about the human preferences they are required to satisfy. Such machines would be humble, altruistic, and committed to pursue our objectives, not theirs. This new foundation would allow us to create machines that are provably deferential and provably beneficial.In a 2014 editorial co-authored with Stephen Hawking, Russell wrote, "Success in creating AI would be the biggest event in human history. Unfortunately, it might also be the last." Solving the problem of control over AI is not just possible; it is the key that unlocks a future of unlimited promise.

     He was a full time retail employee with dreams of becoming a professional gamer. But little did he know that his perfect woman was about to travel back in time to change history. This is a stand alone novel.

    He looks like us, he lives like us... but he is not one of us. Kalian knows nothing outside of his mundane life teaching history on 30th century Earth, until a day like any other triggers a series of events, which will tie his fate to that of humanity. A human hand print, embedded into a rock with alien script, is discovered on a moon that mankind has never set foot on. This discovery holds a secret, which will sweep Kalian into the heart of a conspiracy that has corrupted the galaxy for two hundred thousand years.

    One unforgettable journey. Their programming will never be the same. Cog looks like a normal twelve-year-old boy. But his name is short for “cognitive development,” and he was built to learn.But after an accident leaves him damaged, Cog wakes up in an unknown lab—and Gina, the scientist who created and cared for him, is nowhere to be found. Surrounded by scientists who want to study him and remove his brain, Cog recruits four robot accomplices for a mission to find her.Cog, ADA, Proto, Trashbot, and Car’s journey will likely involve much cognitive development in the form of mistakes, but Cog is willing to risk everything to find his way back to Gina.

    Algorithms have made our lives more efficient, more entertaining, and, sometimes, better informed. At the same time, complex algorithms are increasingly violating the basic rights of individual citizens. Allegedly anonymized datasets routinely leak our most sensitive personal information; statistical models for everything from mortgages to college admissions reflect racial and gender bias. Meanwhile, users manipulate algorithms to "game" search engines, spam filters, online reviewing services, and navigation apps.Understanding and improving the science behind the algorithms that run our lives is rapidly becoming one of the most pressing issues of this century. Traditional fixes, such as laws, regulations and watchdog groups, have proven woefully inadequate. Reporting from the cutting edge of scientific research, The Ethical Algorithm offers a new approach: a set of principled solutions based on the emerging and exciting science of socially aware algorithm design. Michael Kearns and Aaron Roth explain how we can better embed human principles into machine code - without halting the advance of data-driven scientific exploration. Weaving together innovative research with stories of citizens, scientists, and activists on the front lines, The Ethical Algorithm offers a compelling vision for a future, one in which we can better protect humans from the unintended impacts of algorithms while continuing to inspire wondrous advances in technology.

    Often humorously fumbling in his interactions with people, André analyzes his experiences, attempting to understand the faults and foibles of human personality. Accompanied by his girlfriend, Dr. Margaret 13, a droid physician of his own creation, André achieves a position as translator and self-appointed mendacity-monitor to the American President and strives to save humans from themselves.

    The artificial intelligence system, created by DeepMind, had been fed nothing but the rules of the Royal Game when it beat the world’s strongest chess engine in a prolonged match. The selection of ten games published in December 2017 created a worldwide sensation: how was it possible to play in such a brilliant and risky style and not lose a single game against an opponent of superhuman strength?For Game Changer, Matthew Sadler and Natasha Regan investigated more than two thousand previously unpublished games by AlphaZero. They also had unparalleled access to its team of developers and were offered a unique look ‘under the bonnet’ to grasp the depth and breadth of AlphaZero’s search. Sadler and Regan reveal its thinking process and tell the story of the human motivation and the techniques that created AlphaZero.Game Changer also presents a collection of lucidly explained chess games of astonishing quality. Both professionals and club players will improve their game by studying AlphaZero’s stunning discoveries in every field that matters: opening preparation, piece mobility, initiative, attacking techniques, long-term sacrifices and much more.The story of AlphaZero has a wider impact. Game Changer offers intriguing insights into the opportunities and horizons of Artificial Intelligence. Not just in solving games, but in providing solutions for a wide variety of challenges in society.With a foreword by former World Chess Champion Garry Kasparov and an introduction by DeepMind CEO Demis Hassabis.Matthew Sadler (1974) is a Grandmaster who twice won the British Championship and was awarded an individual Gold Medal at the 1996 Olympiad. He has authored several highly acclaimed books on chess and has been writing the famous ‘Sadler on Books’ column for New In Chess magazine for many years. Natasha Regan is a Women’s International Master from England who achieved a degree in mathematics from Cambridge University. Matthew Sadler and Natasha Regan won the English Chess Federation 2016 Book of the Award for their book Chess for Life.

    All across the frontier, other worlds have succumbed to the relentless attacks of robotic alien warships, while hundreds of light years away, the core of human civilization—those star systems closest to Earth, known as the Hallowed Vasties—have all fallen to ruins. Powerful telescopes can see only dust and debris where once there were orbital mega-structures so huge they eclipsed the light of their parent stars.No one knows for sure what caused the Hallowed Vasties to fail, but a hardened adventurer named Urban intends to find out. He has the resources to do it. He commands a captive alien starship fully capable of facing the dangers that lie beyond Deception Well.With a ship’s company of explorers and scientists, Urban is embarking on a voyage of re-discovery. They will be the first in centuries to confront the hazards of an inverted frontier as they venture back along the path of human migration. Their goal: to unravel the mystery of the Hallowed Vasties and to discover what monstrous life might have grown up among the ruins.Edges is a new entry point into the classic story world of Linda Nagata’s The Nanotech Succession.

    As Carl Benedikt Frey shows, the Industrial Revolution created unprecedented wealth and prosperity over the long run, but the immediate consequences of mechanization were devastating for large swaths of the population. Middle-income jobs withered, wages stagnated, the labor share of income fell, profits surged, and economic inequality skyrocketed. These trends, Frey documents, broadly mirror those in our current age of automation, which began with the Computer Revolution.Just as the Industrial Revolution eventually brought about extraordinary benefits for society, artificial intelligence systems have the potential to do the same. But Frey argues that this depends on how the short term is managed. In the nineteenth century, workers violently expressed their concerns over machines taking their jobs. The Luddite uprisings joined a long wave of machinery riots that swept across Europe and China. Today’s despairing middle class has not resorted to physical force, but their frustration has led to rising populism and the increasing fragmentation of society. As middle-class jobs continue to come under pressure, there’s no assurance that positive attitudes to technology will persist.The Industrial Revolution was a defining moment in history, but few grasped its enormous consequences at the time. The Technology Trap demonstrates that in the midst of another technological revolution, the lessons of the past can help us to more effectively face the present.

    The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard.Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

    This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach.Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use.Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow LiteDevelop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google CoralExplore fun projects, from Silicon Valley's Not Hotdog app to 40+ industry case studiesSimulate an autonomous car in a video game environment and build a miniature version with reinforcement learningUse transfer learning to train models in minutesDiscover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users

     He lives in a corrupt, church-controlled dystopia, his family is soon broken, and the only joy to be had comes from the escapism of his full-immersion gaming. Introduced to a new and very illegal game, he finds himself in the body of a dragon, on a quest to find a dark and evil power to serve. But the game is more than it seems, and the dragon is more than a beast. Soon Rich's life is far, far more complicated than he ever expected. And the threats against him grow, both in-game and in realspace. There is no path that will not lead to blasphemy. And the dark secrets revealed will change two worlds, before all is done... A new litrpg saga, set in Threadbare's world of Generica Online.Illustrator: Amelia Parris

    Recent advances in the field have shown how it's possible to teach a machine to excel at human endeavors--such as drawing, composing music, and completing tasks--by generating an understanding of how its actions affect its environment.With this practical book, machine learning engineers and data scientists will learn how to recreate some of the most famous examples of generative deep learning models, such as variational autoencoders and generative adversarial networks (GANs). You'll also learn how to apply the techniques to your own datasets.David Foster, cofounder of Applied Data Science, demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to the most cutting-edge algorithms in the field. Through tips and tricks, you'll learn how to make your models learn more efficiently and become more creative.Get a fundamental overview of deep learningLearn about libraries such as Keras and TensorFlowDiscover how variational autoencoders workGet practical examples of generative adversarial networks (GANs)Understand how autoregressive generative models functionApply generative models within a reinforcement learning setting to accomplish tasks

    What if the Twelve Dancing Princesses were undead clones? What if the witch in Hansel and Gretel was an AI-sentient house? Are you ready for the Three Little Pigs… in space? These fourteen tales will entertain and inspire you, and you’ll never see your favorite faerie tales quite the same way again. Grab your copy of Once Upon A Star, and don’t forget the other anthologies - Once Upon A Curse, Once Upon A Kiss, and Once Upon A Quest - for more magical retellings!

    Somehow, they didn't upload her memories alone. They uploaded the most important part of her--her consciousness. As she struggles to find out what happened to her, she must also come to grips with the virtual reality nature of her existence.  Her body died, but she sure hasn't. What does it mean to be alive, then? She wants to talk to her friends and family, but convincing them she's real won't be easy. First, she has to get the people in control of the network to recognize that she's a real person, trapped inside their technology.She needs to establish a hello protocol--a way of establishing communication. To do so, she'll have to become more powerful than she ever dreamed.You'll be on the edge of your seat as you learn to take control of this fascinating new existence with Jennika. Begin the adventure today!

    After the discovery of intergalactic travel technology, humankind initiates a mission to the four most likely habited planets in order to bring their own civilization to the next maturity level. ‘Keat’ who has a deep interest in the “big questions” of life is part of the first mission which turns their wealthy, human civilization upside down without facing any enemies.

    His body reconstructed by doctors, twice. The future has always been rough, but is this going too far? Someone keeps murdering the richest man on the planet Smuds and he wants it stopped. There is one detective marshal in Port City. One hope. Can Marshal Harry and her deputies solve the murders before someone polishes the thrice murdered man off for good? That's him in the jar on the cover, by the way. These and many other questions answered, when you buy this book.

    Now he could be humankind’s only hope of stopping the end of our species…Special Forces Captain Cade Rearden struggles to control the whispers in his head. Plagued by Multiple Personality Disorder, he nearly spirals into insanity after extremists kill his whole team and hold him captive. Defeated but not broken, he can hardly believe it when an artificial intelligence named Doris rescues him, then recruits him for an impossible mission.Pulling together a crack military team, Rearden must take down Janus, a rogue AI intent on launching a chain of deadly attacks on American soil. And the key to staying one step ahead of the enemy could lie in understanding and protecting the incredible knowledge Doris possess. Knowledge that didn’t originate here on Earth.Can Rearden somehow control his internal chaos and the battles raging around him? Can he and his team prevent the genocide of the whole human race? The stakes don’t get much higher.State of Chaos is the first book in the riveting Cade Rearden science fiction thriller series. If you like near-future technology, complex heroes, and high-octane action, then you’ll love JK Franks’ explosive adventure.Buy State of Chaos to join the fight against an AI Apocalypse today!

    Over a while, I have improvised my response based on the follow-up questions they ask like: 1. What is the difference between DS, ML, DL, AI, DM? 2. What are the roles in DS/AI, who does what? 3. What concepts, processes & tools they need to learn? 4. Which books, courses, etc they need to refer to? 5. How to build a DS/AI portfolio? 6. How to write a resume for DS/AI? 7. How to build a helpful network?8. How to search for the job? 9. How to prepare for the interview? 10. How to stay up to date in this still-evolving field? You can notice that these questions are not conceptual ones and there is no dedicated material to address these roadblocks. How about a book or course that gives you enough exposure to the DS/AI field that you can yourself analyze what is needed for you and build your own roadmap? My answer to the above question is this book. This book covers the framework to launch your DS/AI career in 8 chapters.

    The Curse- every fifty years the Full Mental Packet Bar is robbed. Happens like clockwork. But this time the robbery involves two murders. Enter Harry, the only homicide detective marshal on the planet, and her heavily armed sidekick, Chunglie. His job is to keep Harry alive long enough to find the murderer. When the Rehd Shirts attack, the city is in flames and the bodies are dropping from the flies, onto the bar flies, Whodunnit and Whydunnit seems the least of their problems. Can even Harry and Chunglie survive this one? Buy now to find out.

    His work was motivated not only by technological advancement but also by the desire to understand the workings of our own minds. Minsky's insights about the mind provide fresh perspectives on education and how children learn. This book collects for the first time six essays by Minsky on children, learning, and the potential of computers in school to enrich children's development. In these essays Minsky discusses the shortcomings of conventional education (particularly in mathematics) and considers alternative approaches; reflects on the role of mentors; describes higher-level strategies for thinking across domains; and suggests projects for children to pursue. Each essay is paired with commentary by one of Minsky's former colleagues or students, which identifies Minsky's key ideas and connects his writings to current research. Minsky once observed that in traditional teaching, "instead of promoting inventiveness, we focus on preventing mistakes." These essays offer Minsky's unique insights into how education can foster inventiveness.Commentary by Hal Abelson, Walter Bender, Alan Kay, Margaret Minsky, Brian Silverman, Gary Stager, Mike Travers, Patrick Henry Winston

    The book approaches optimization from an engineering perspective, where the objective is to design a system that optimizes a set of metrics subject to constraints. Readers will learn about computational approaches for a range of challenges, including searching high-dimensional spaces, handling problems where there are multiple competing objectives, and accommodating uncertainty in the metrics. Figures, examples, and exercises convey the intuition behind the mathematical approaches. The text provides concrete implementations in the Julia programming language.Topics covered include derivatives and their generalization to multiple dimensions; local descent and first- and second-order methods that inform local descent; stochastic methods, which introduce randomness into the optimization process; linear constrained optimization, when both the objective function and the constraints are linear; surrogate models, probabilistic surrogate models, and using probabilistic surrogate models to guide optimization; optimization under uncertainty; uncertainty propagation; expression optimization; and multidisciplinary design optimization. Appendixes offer an introduction to the Julia language, test functions for evaluating algorithm performance, and mathematical concepts used in the derivation and analysis of the optimization methods discussed in the text. The book can be used by advanced undergraduates and graduate students in mathematics, statistics, computer science, any engineering field, (including electrical engineering and aerospace engineering), and operations research, and as a reference for professionals.

    This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special marices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

    Analyzing myriad technologies, from sex robots and military drones to sharing-economy platforms, Atanasoski and Vora show how liberal structures of antiblackness, settler colonialism, and patriarchy are fundamental to human---machine interactions, as well as the very definition of the human. While these new technologies and engineering projects promise a revolutionary new future, they replicate and reinforce racialized and gendered ideas about devalued work, exploitation, dispossession, and capitalist accumulation. Yet, even as engineers design robots to be more perfect versions of the human—more rational killers, more efficient workers, and tireless companions—the potential exists to develop alternative modes of engineering and technological development in ways that refuse the racial and colonial logics that maintain social hierarchies and inequality.

    During that time mankind's greatest programming - the AI - multiplied themselves on the internet and on any server they could find. They were able to modify and enhance their abilities far beyond human comprehension. Modern-day AI are capable of thinking on their own, making decisions, and can even feel emotion. These advanced programs are used in many different ways - in the medical field to make drastic advances in medicine and genetic alterations, as assistants or for companionship. There are even AI that serve in high rank positions of mankind's society. One of these higher-ranking AI is in charge of a secret, special ops unit in the United States Army. Monty is her name and her commands must be obeyed without question. Dunstan is a human soldier under Monty's command, and he and his team are about to go on a recon mission on foreign soil. The mission goes horribly sideways and under the best of circumstances would be a catastrophic failure; however Dunstan and his team are far from normal.

    He's the Last Human. He's rich, he's famous, and he hates his life. The year 2056, WW3 has come and gone, and machines have transformed the Earth and its people. Some might say for the better. Not Rick. Rick is the last human, kept and paraded around as a reminder of the inferiority of the ape-like humans. Rick wants out. But he’s not getting away so easily, the Agency is not letting its puppet go. Follow Rick as he tries to sober up long enough to escape from his lavish lifestyle only to end up entangled in interplanetary intrigue. In a world of super-cyborgs and mutants, Rick will show them the meaning of humanity as he travels far and wide testing the fabric of society in an attempt to find himself or whatever it is he’s looking for. Warning, adult content. Do not read if easily offended. This book contains coarse language, sex, drugs and violence. All the good stuff. Head over to my blog and read some more of my nonsense there. The first post is about writing and the second editing, maybe you’ll find them interesting, educational or even funny, maybe not. If you want to find out about why I write and my process head over to https://www.thelasthuman.co/blog Bio T.F.R. LeBoomington resides between London and France. When he’s not working on some mad project he's out researching his books and studying humans in their natural drinking environments. Throughout the years he's worked in marketing, video production, gaming, smart homes and more. His passion for technology and knowledge of the tech industry is geeky. He's been writing since he was kid, but never attempted to publish anything until 10 years ago when he tried and failed miserably. (See Why I Write Blog Post) A couple of years ago he decided to start writing again, on the side. The result is The Last Human Saga. It's a product of his love of 80s and 90s pop culture mixed with his love of futurism and science-fiction, filtered through his life experience. That being said he is insane and so is his writing. Thankfully his editor is a physicist and savage critic.

    AI is now driving our cars, running our factories, and winning our game shows. There are many opportunities to take advantage of this nascent technology, but these opportunities require a knowledge of what AI is and how it can solve your problems. The Future of Business is your guide to the revolution. It will explain what AI is, where it came from, and how it can be used to solve a wide array of problems.

    This book provides a comprehensive introduction for data scientists and software engineers with machine learning experience. You'll start with deep learning basics and move quickly to the details of important advanced architectures, implementing everything from scratch along the way.Author Seth Weidman shows you how neural networks work using a first principles approach. You'll learn how to apply multilayer neural networks, convolutional neural networks, and recurrent neural networks from the ground up. With a thorough understanding of how neural networks work mathematically, computationally, and conceptually, you'll be set up for success on all future deep learning projects.This book provides:Extremely clear and thorough mental models--accompanied by working code examples and mathematical explanations--for understanding neural networksMethods for implementing multilayer neural networks from scratch, using an easy-to-understand object-oriented frameworkWorking implementations and clear-cut explanations of convolutional and recurrent neural networksImplementation of these neural network concepts using the popular PyTorch framework

    But where to start? It’s easy to be intimidated, even as a software developer. The good news is that it doesn’t have to be that hard. Master machine learning by writing code one line at a time, from simple learning programs all the way to a true deep learning system. Tackle the hard topics by breaking them down so they’re easier to understand, and build your confidence by getting your hands dirty.

    if you want to understand how the concept of life is changing, read this' Professor Andrew Briggs, University of OxfordWhen Darwin set out to explain the origin of species, he made no attempt to answer the deeper question: what is life? For generations, scientists have struggled to make sense of this fundamental question. Life really does look like magic: even a humble bacterium accomplishes things so dazzling that no human engineer can match it. And yet, huge advances in molecular biology over the past few decades have served only to deepen the mystery. So can life be explained by known physics and chemistry, or do we need something fundamentally new?In this penetrating and wide-ranging new analysis, world-renowned physicist and science communicator Paul Davies searches for answers in a field so new and fast-moving that it lacks a name, a domain where computing, chemistry, quantum physics and nanotechnology intersect. At the heart of these diverse fields, Davies explains, is the concept of information: a quantity with the power to unify biology with physics, transform technology and medicine, and even to illuminate the age-old question of whether we are alone in the universe.From life's murky origins to the microscopic engines that run the cells of our bodies, The Demon in the Machine is a breath-taking journey across the landscape of physics, biology, logic and computing. Weaving together cancer and consciousness, two-headed worms and bird navigation, Davies reveals how biological organisms garner and process information to conjure order out of chaos, opening a window on the secret of life itself.

    After covering the basics, you’ll see how to collect user data and produce personalized recommendations. You’ll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book covers scaling problems and other issues you’ll encounter as your site grows.

    Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size--small enough to run on a microcontroller. With this practical book you'll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices.Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary.Build a speech recognizer, a camera that detects people, and a magic wand that responds to gesturesWork with Arduino and ultra-low-power microcontrollersLearn the essentials of ML and how to train your own modelsTrain models to understand audio, image, and accelerometer dataExplore TensorFlow Lite for Microcontrollers, Google's toolkit for TinyMLDebug applications and provide safeguards for privacy and securityOptimize latency, energy usage, and model and binary size

    This practical book examines real-world scenarios where DNNs--the algorithms intrinsic to much of AI--are used daily to process image, audio, and video data.Author Katy Warr considers attack motivations, the risks posed by this adversarial input, and methods for increasing AI robustness to these attacks. If you're a data scientist developing DNN algorithms, a security architect interested in how to make AI systems more resilient to attack, or someone fascinated by the differences between artificial and biological perception, this book is for you.Delve into DNNs and discover how they could be tricked by adversarial inputInvestigate methods used to generate adversarial input capable of fooling DNNsExplore real-world scenarios and model the adversarial threatEvaluate neural network robustness; learn methods to increase resilience of AI systems to adversarial dataExamine some ways in which AI might become better at mimicking human perception in years to come

    

    With important practical applications to computer science and industry, computational complexity theory has evolved into a highly interdisciplinary field, with strong links to most mathematical areas and to a growing number of scientific endeavors.Avi Wigderson takes a sweeping survey of complexity theory, emphasizing the field’s insights and challenges. He explains the ideas and motivations leading to key models, notions, and results. In particular, he looks at algorithms and complexity, computations and proofs, randomness and interaction, quantum and arithmetic computation, and cryptography and learning, all as parts of a cohesive whole with numerous cross-influences. Wigderson illustrates the immense breadth of the field, its beauty and richness, and its diverse and growing interactions with other areas of mathematics. He ends with a comprehensive look at the theory of computation, its methodology and aspirations, and the unique and fundamental ways in which it has shaped and will further shape science, technology, and society. For further reading, an extensive bibliography is provided for all topics covered.Mathematics and Computation is useful for undergraduate and graduate students in mathematics, computer science, and related fields, as well as researchers and teachers in these fields. Many parts require little background, and serve as an invitation to newcomers seeking an introduction to the theory of computation. Comprehensive coverage of computational complexity theory, and beyond High-level, intuitive exposition, which brings conceptual clarity to this central and dynamic scientific discipline Historical accounts of the evolution and motivations of central concepts and models A broad view of the theory of computation's influence on science, technology, and society Extensive bibliography

    Then, you'll discover how to train a Python-based NLP machine to recognize patterns and extract information from text. As you explore the carefully-chosen examples, you'll expand your machine's knowledge and apply it to a range of challenges, from building a search engine that can find documents based on their meaning rather than merely keywords, to training a chatbot that uses deep learning to answer questions and participate in a conversation.

    Video games already depend on AI. We use games to test AI algorithms, challenge our thinking, and better understand both natural and artificial intelligence. In the future, Togelius argues, game designers will be able to create smarter games that make us smarter in turn, applying advanced AI to help design games. In this book, he tells us how.Games are the past, present, and future of artificial intelligence. In 1948, Alan Turing, one of the founding fathers of computer science and artificial intelligence, handwrote a program for chess. Today we have IBM's Deep Blue and DeepMind's AlphaGo, and huge efforts go into developing AI that can play such arcade games as Pac-Man. Programmers continue to use games to test and develop AI, creating new benchmarks for AI while also challenging human assumptions and cognitive abilities. Game design is at heart a cognitive science, Togelius reminds us—when we play or design a game, we plan, think spatially, make predictions, move, and assess ourselves and our performance. By studying how we play and design games, Togelius writes, we can better understand how humans and machines think. AI can do more for game design than providing a skillful opponent. We can harness it to build game-playing and game-designing AI agents, enabling a new generation of AI-augmented games. With AI, we can explore new frontiers in learning and play.

    Your smartphone that suggests you the next word you want to type, your Netflix account that recommends you the series you may like or Spotify’s personalised playlists. This is how machines are learning from you in everyday life. And these examples are only the surface of this technological revolution. Either if you want to start your own AI entreprise, to empower your business or to work in the greatest and most innovative companies, Artificial Intelligence is the future, and Neural Networks programming is the skill you want to have. The good news is that there is no exclusive club, you can easily (if you commit, of course) learn how to program and use neural networks, and to do that Neural Networks for Beginners is the perfect way. In this book you will learn: The types and components of neural networks The smartest way to approach neural network programming Why Algorithms are your friends The “three Vs” of Big Data (plus two new Vs) How machine learning will help you making predictions  The three most common problems with Neural Networks and how to overcome them Even if you don’t know anything about programming, Neural Networks is the perfect place to start now. Still, if you already know about programming but not about how to do it in Artificial Intelligence, neural networks are the next thing you want to learn. And Neural Networks for Beginners is the best way to do it. Download Neural Network for Beginners now to get the best start for your journey to Artificial Intelligence. Scroll to the top of the page and click the BUY NOW button.

    Do humans even stand a chance? Or will they meet their digital doom? In The Robot Revolution, Danger Dan, Gadget Girl and Power Paws have to abandon all gadgets and rely solely on their imagination and wits to fight the technological takeover. Can they power through and pull the plug on the deadly machines? Sparks will fly, smoke will rise, smog will smother Singapore, in this epic battle!

    The book will also guide you on how to implement various machine learning algorithms for classification, clustering, and recommendation engines, using a recipe-based approach. With emphasis on practical solutions, dedicated sections in the book will help you to apply supervised and unsupervised learning techniques to real-world problems. Toward the concluding chapters, you will get to grips with recipes that teach you advanced techniques including reinforcement learning, deep neural networks, and automated machine learning.By the end of this book, you will be equipped with the skills you need to apply machine learning techniques and leverage the full capabilities of the Python ecosystem through real-world examples. What you will learn Use predictive modeling and apply it to real-world problems Explore data visualization techniques to interact with your data Learn how to build a recommendation engine Understand how to interact with text data and build models to analyze it Work with speech data and recognize spoken words using Hidden Markov Models Get well versed with reinforcement learning, automated ML, and transfer learning Work with image data and build systems for image recognition and biometric face recognition Use deep neural networks to build an optical character recognition system Who this book is for This book is for data scientists, machine learning developers, deep learning enthusiasts and Python programmers who want to solve real-world challenges using machine-learning techniques and algorithms. If you are facing challenges at work and want ready-to-use code solutions to cover key tasks in machine learning and the deep learning domain, then this book is what you need. Familiarity with Python programming and machine learning concepts will be useful. Table of Contents The Realm of Supervised Learning Constructing a Classifier Predictive Modeling Clustering with Unsupervised Learning Visualizing Data Building Recommendation Engines Analyzing Text Data Speech Recognition Dissecting Time Series and Sequential Data Image Content Analysis Biometric Face Recognition Reinforcement Learning Techniques Deep Neural Networks Unsupervised Representation Learning Automated machine learning and Transfer learning Unlocking Production issues

    It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language.In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras.By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands. What you will learn Handle files and images, and explore various image processing techniques Explore image transformations, including translation, resizing, and cropping Gain insights into building histograms Brush up on contour detection, filtering, and drawing Work with Augmented Reality to build marker-based and markerless applications Work with the main machine learning algorithms in OpenCV Explore the deep learning Python libraries and OpenCV deep learning capabilities Create computer vision and deep learning web applications Who this book is for This book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must. Table of Contents Setting up OpenCV Image basics in OpenCV Handling files and images Constructing basic shapes in OpenCV Image processing techniques Constructing and Building Histograms Thresholding techniques Contours Detection, filtering, and drawing Augmented reality and 3D Visualization Machine Learning and Deep Learning in OpenCV Face detection, tracking and recognition Introduction to deep learning Mobile and web computer vision with Python and OpenCV

    In this engaging guide written for business leaders and technology pros alike, authors and AI experts Nicolò Valigi and Gianluca Mauro use fascinating projects, hands-on activities, and real-world explanations to make it clear how your business can benefit from AI.

    It emphasizes contemporary data-driven approaches, focusing on techniques from supervised and unsupervised machine learning. The first section establishes a foundation in machine learning by building a set of tools that will be used throughout the book and applying them to word-based textual analysis. The second section introduces structured representations of language, including sequences, trees, and graphs. The third section explores different approaches to the representation and analysis of linguistic meaning, ranging from formal logic to neural word embeddings. The final section offers chapter-length treatments of three transformative applications of natural language processing: information extraction, machine translation, and text generation. End-of-chapter exercises include both paper-and-pencil analysis and software implementation.The text synthesizes and distills a broad and diverse research literature, linking contemporary machine learning techniques with the field's linguistic and computational foundations. It is suitable for use in advanced undergraduate and graduate-level courses and as a reference for software engineers and data scientists. Readers should have a background in computer programming and college-level mathematics. After mastering the material presented, students will have the technical skill to build and analyze novel natural language processing systems and to understand the latest research in the field.

    An expert in computer science and media explains the present and future of a world in which news is created by algorithm.Amid the push for self-driving cars and the roboticization of industrial economies, automation has proven one of the biggest news stories of our time. Yet the wide-scale automation of the news itself has largely escaped attention. In this lively expos� of that rapidly shifting terrain, Nicholas Diakopoulos focuses on the people who tell the stories--increasingly with the help of computer algorithms that are fundamentally changing the creation, dissemination, and reception of the news.Diakopoulos reveals how machine learning and data mining have transformed investigative journalism. Newsbots converse with social media audiences, distributing stories and receiving feedback. Online media has become a platform for A/B testing of content, helping journalists to better understand what moves audiences. Algorithms can even draft certain kinds of stories. These techniques enable media organizations to take advantage of experiments and economies of scale, enhancing the sustainability of the fourth estate. But they also place pressure on editorial decision-making, because they allow journalists to produce more stories, sometimes better ones, but rarely both.Automating the News responds to hype and fears surrounding journalistic algorithms by exploring the human influence embedded in automation. Though the effects of automation are deep, Diakopoulos shows that journalists are at little risk of being displaced. With algorithms at their fingertips, they may work differently and tell different stories than they otherwise would, but their values remain the driving force behind the news. The human-algorithm hybrid thus emerges as the latest embodiment of an age-old tension between commercial imperatives and journalistic principles.

    And Marxist analysis has to keep up: while machines were always central to Marxist analysis, modern AI is a new kind of machine that Marx could not have anticipated.             Inhuman Power explores the relationship between Marxist theory and AI through three approaches, each using the lens of a different Marxist theoretical concept. While the idea of widespread AI tends to be celebrated as much as questioned, a deeper analysis of its reach and potential produces a more complex and disturbing picture than has been identified. Inhuman Power argues that on its current trajectory, AI is likely to render humanity obsolete and that the only way to prevent it is a communist revolution.

    And once you have an understanding of what AI is, you can move forward in your journey to create better informed industry-level business AI applications. The book bundle includes: Learning to teach machines to learn! Are you intrigued by the fact that artificial intelligence poses an existential threat to human beings and has been around for at least 60 years? If yes, then here is the best introductory review of Artificial Intelligence and its effects on human behavior and the market. The book is thoroughly examined, neatly composed, significantly intriguing, and insightful. Help yourself understand the concepts of AI and get insights regarding:●      A brief history of artificial intelligence●      The state of art of machine learning●      Artificial neural networks applied to machine learning●      How to build an AI-ready culture●      Effects of AI on our daily lives Adding persistent spirit to your business! Do you often come up with some innovative techniques to lead the industry? If yes, then this book is made for you! It will familiarize you with the advances in industry-level AI and will open your understanding of what to expect in sales shortly. Here is a preview of what you will learn:●      How AI can transform your business●      The correct mindset for social media marketing●      The epoch of chatbots●      How AI can help with recruitment●      Which platforms will best fit business in 2020●      How AI helps in predicting consumer behavior patterns And More ….. Would You Like To Know More? Scroll to the top of the page and select the buy now button.