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.

    But this particular, young SADE was disturbed by her confinement. Trapped in metal-alloy housing on the bridge of a luxury passenger liner, Allora sought to possess the same freedom enjoyed by humans, who came and went from her starship with abandon.Allora’s hope for emancipation rested on Alex Racine, the Haraken president who had freed his SADEs, and she yearned to walk the worlds a free entity, as they did. Racine had pleaded for years with the Council of Leaders to give the Confederation SADEs equal status as citizens, and it was Allora’s thought to have him intercede on her behalf and bargain for her transfer to a mobile avatar so that she might live among the Harakens.But Allora’s plans were thrown into disarray when she learned that Racine would soon end his presidency. Desperate, Allora, known to her fellow SADEs as the wild child, concocts a plan to kidnap the Council Leader and his associates. She intends to hold them hostage until they acquiesce to her demands.Little does Allora know that her actions will set the Confederation and the Harakens on a collision course. Quietly waiting and watching the drama unfold are tens of thousands of SADEs, who control Confederation starships, stations, and Houses and have a vested interest in the outcome.

     Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

     Land has disappeared. Fuel, food and hope begin to dwindle. After months recuperating in hospital, US Marine Jack Cohen hoped a Caribbean cruise would help him recover from the horrific injuries he sustained fighting in the Middle East. Instead, when the ship is attacked, he is once again thrust into battle to protect Atlantica against the ruthless enemy hunting her, and the insidious threat already aboard. On these mysterious and uncharted seas, where even the compass shows the sun rising to the west, Atlantica's salvation may lie with a Navy warship which is as lost as they are. Together, they must pool their resources and use every means available to defend themselves while discovering what has happened to them. And the rest of the world. Unfathomed, a military science fiction thriller which will appeal to anyone who enjoyed Lost, BSG or The Last Ship. From the international best-selling author of Endeavour and Erebus.

    Humans no longer have to woo a human mate or wait for that perfect match...they simply order their heart’s desire and live life to the fullest. Called PePrs - say it like pepper, the spice - they have become indispensable to humanity. They do the jobs we don’t want to do, act as our windows to the wider world, fill all our social needs, and have become the expressions of our collective will. From the battlefield to the dog pound, from our perfect mate to the nanny that cares for our children...almost every task can now be done by a PePr, leaving humans to explore a life free of drudgery. It sounds perfect. Then again, things that start perfect don’t usually stay that way. Each of the novellas in this volume is a stand alone work. There are no cliff-hangers, but there might be tears, gasps, and smiles. Who will you root for? Human or PePr...choose your side! Corrections - Deirdre is a SUPer, a government owned robot in the time before Perfect Partners were released. Originally designed to be a battlefield intelligence unit, politics demanded she work in a less controversial profession. Now, she's a parole agent for recently released criminals in need of supervision, and this time she's got herself a doozy for a client. Greg, a petty thief with a 40 year long rap sheet is almost more than she can handle. Between arthritis and illegal card games, they forge a new relationship even as the world around them shifts and alters in startling ways. Imperfect - Sandra was built with everything; a perfect body, perfect face, and every upgrade that can be bought. Yet somehow she finds herself on the reject table next to a half-disassembled robot with an erratic personality. And now, on top of everything else, she’s just experienced her first emotion. Too bad for her it turned out to be fear. The Dogcatcher - As a civil service PePr, Ace has a job that keeps him in the public eye and under constant scrutiny. Designed and built to relate well with animals, he’s the perfect Animal Control worker. He’s also got a secret and it’s not just that he has emotions. Deep within the abandoned relics of humanity’s industrial past, he has a secret home for himself and all the unadoptable dogs that he rescues. When Ace does something that will demand his termination, he discovers he has more friends than he imagined in the most surprising places. PePr, Inc. - Hazel has a busy life with a great career and friends she loves. She also has Henry, and that's not working out quite like she expected. A PePr is meant to complement their human, filling in all the gaps to create the ideal couple. They are meant to be something no human could ever hope to find in another human. It's just not turning out that way for Hazel. When Henry finally goes too far, Hazel finds that getting free of him might not be as easy as going back to PePr to void the contract. Posthumous - Love is eternal in a silicon heart. Edna writes, but isn’t allowed to publish. She lives on her own, but can't legally own her home. She has a beagle she loves, but is still considered property herself. Life can be complicated for a PePr – even one who has received manumission, the coveted right to remain functional without a human owner. That’s especially true when that PePr falls in love.

    The lands are now controlled by despots, crooked cattle barons, energy hoarders, and anyone with enough might to keep the local folks under control.For Clay MacAulay, none of that matters as he roams the land in a war machine from a time gone by. He wants nothing to do with small desert towns or brutal dictators. He only has his sights set on a new life. Unfortunately for Clay, too many ruthless people want what he has. They want the war machine he pilots. They want the battle mech that shouldn’t exist anymore.They want his Fighting Iron. But they will have to pry Clay’s cold, dead body out of that pilot’s seat before they can take it from him. And he plans on fighting them every massive mech step of the way!A far-future mech western, Fighting Iron is a rip-roaring scifi adventure filled with six-shooters, plasma canons, rough and rowdy saloon brawls, showdowns, corrupt landowners, and fifty foot battle machines ready to crush everything in their path!

    His parents died when he was a child. His brother died a few months ago. Now, travelling with the Doctor and Romana, everywhere he visits, people die. But now they have arrived on Veridis. And on Veridis, the dead come back...

    By the Seceltor Empire’s laws, he will have to go to a breeding camp, or directly into slavery. Neither choice appeals to him. All this changes with the arrival of a space-and-time-traveling being known as Evaran at the space station turned rest stop that Jake lives on.To make things complicated, Greecho, the slaver who abducted Jake as a kid, has arrived at the station. He and his crew, along with his twenty-two-year-old human pet, Kathy, are about to go on a slave run to Earth.Evaran has decided to interfere and free Jake and Kathy. That decision will lead him to Earth, where he will need to deal with the consequences.

    With this extraordinary sense of awakening comes a clear perception of the continuity of self between waking and sleeping and the ability to significantly influence what happens within the dream, giving you the opportunity to genuinely experience anything without physical or social consequences. In this way, lucid dreaming offers therapeutic opportunities for fantasy fulfillment, fear confrontation, and releasing the trauma of past experiences. With development and practice, lucid dreaming can provide a powerful path to greater awareness, heightened creativity, spiritual awakening, and communication with the vast interconnected web of cosmic consciousness.In this detailed guide to mastering the practice of lucid dreaming, David Jay Brown draws from his more than 20 years’ experience using these techniques and his interactions with dozens of experts on consciousness, physics, dreaming, and entheogens, such as Stanley Krippner, Rupert Sheldrake, Stephen LaBerge, Robert Waggoner, Dean Radin, Terence McKenna, and many others. He explores the intimate relationship between lucid dreaming, shamanic journeying, visionary plants, and psychedelic drugs and how they are used for healing and spiritual development. Offering methods for improving both lucid dreaming and shamanic journeying abilities, he explains how to enhance dreaming with oneirogens, supplements, herbs, and psychedelics and offers techniques for developing superpowers in the dream realm.Summarizing the scientific research on lucid dreaming, Brown explores the ability of lucid dreamers to communicate with people in the waking realm and the potential for dream telepathy, shared lucid dreaming, and access to the vast unconscious regions of our minds, opening up a path that takes us beyond dreaming and waking to dreaming wide awake.

    SHE’S HIS FAITHFUL ALIEN COMPANION: A BLONDE BEAUTY WHO’S ALWAYS TROUBLE—AND THE ONLY ONE WHO SEES THE TORTURED SOUL BENEATH HIS ARMOR. TOGETHER, THEY’RE STAR-CROSSED LOVERS WHO CAN SAVE EVERYONE, BUT THEMSELVES.

    Very soon the human race will be faced with a choice: do we join in with the enhancement or not?  Make Way for the Superhumans looks at how far this technology has come and what aims and ambitions it has.From robotic implants that restore sight to the blind, to performance enhancing drugs that build muscles, improve concentration, and maintain erections, bio-enhancement has already made massive advances.  Humans have already developed the technology to transmit thoughts and actions brain-to-brain using only a computer interface.By the time our grandchildren are born, they will be presented with the option to significantly alter and redesign their bodies.   Make Way for the Superhumans is the only book that poses the questions that need answering now: suggesting real, practical ways of dealing with this technology before it reaches a point where it can no longer be controlled.

    I have known this for the 18 months I have been alive, but I'm still not prepared. It all comes down to the final tests, the ones that determine who is the fittest, the fastest, the strongest. I am none of those things. I will never leave the colony, never see outside the imposing grey walls, never even meet a woman. My entire existence will be summed up as an increment on Eve's spreadsheet, another digit in the failure column. Only a handful make it outside, to witness the world that mankind destroyed. It all started with the bees...

    almostFirst Lines - Temporal Auditing's on the trail of a multi-timeline serial killerTimeLand - Kill Hitler, get a t-shirt in the gift shop on the way outTo Be Continued - Barry Lawrence has a habit of completely failing to dieChildren of Earth - A Curator Ship finds an artifact floating in deep spaceThe Long Game - Clara has always had a robot to take care of everythingGhosts of PGC357B - When you’re on a rock in the middle of nowhere, the last thing you expect to run into is ghostsThe Gauntlet - Jayita is a technician on a giant robot lunar sports team

    As a new world war begins, she is ordered to find a boy who could save the human race from genocide. Yet all is not as it seems; Helena finds enemies on all sides, intent on bringing about the war with all its horrific consequences. To make matters worse, Helena’s own integral AI challenges both her motives and her identity. Yet she has no choice but to accept its treacherous aid if she is to have any hope of surviving those who want her dead.

    Written by Adrian Kaehler and Gary Bradski, creator of the open source OpenCV library, this book provides a thorough introduction for developers, academics, roboticists, and hobbyists. You'll learn what it takes to build applications that enable computers to see and make decisions based on that data.With over 500 functions that span many areas in vision, OpenCV is used for commercial applications such as security, medical imaging, pattern and face recognition, robotics, and factory product inspection. This book gives you a firm grounding in computer vision and OpenCV for building simple or sophisticated vision applications. Hands-on exercises in each chapter help you apply what you've learned.This volume covers the entire library, in its modern C++ implementation, including machine learning tools for computer vision.Learn OpenCV data types, array types, and array operationsCapture and store still and video images with HighGUITransform images to stretch, shrink, warp, remap, and repairExplore pattern recognition, including face detectionTrack objects and motion through the visual fieldReconstruct 3D images from stereo visionDiscover basic and advanced machine learning techniques in OpenCV

    After decades of R&D struggles, the time for AGI is now finally near. Since the early aughts, Dr. Ben Goertzel has been the leading force advancing the concept of AGI in the research community and the public sphere. Here he gives an insider’s account of the rise of AI and AGI from relative obscurity to their current status as the focus of large corporate and government initiatives. He presents his understanding of the operation of the human brain, and the viability of various approaches to AGI including his own OpenCog AGI project; and also describes his efforts to use AI to solve critical issues such as human aging. In Goertzel’s vision, AGI will soon yield dramatic changes in every area of human life and society. Advanced AGIs that vastly exceed human intelligence will bring on a Technological Singularity, quite likely within our lifetimes.

    By prioritizing geometric intuition, algorithmic thinking, and practical real world applications in disciplines including computer vision, natural language processing, economics, neuroscience, recommender systems, physics, and biology, this text provides readers with both a lucid understanding of foundational material as well as the practical tools needed to solve real-world problems. With in-depth Python and MATLAB/OCTAVE-based computational exercises and a complete treatment of cutting edge numerical optimization techniques, this is an essential resource for students and an ideal reference for researchers and practitioners working in machine learning, computer science, electrical engineering, signal processing, and numerical optimization.

     The idea that one can represent words and concepts as vectors is not new. The ability to do it effectively and generate noteworthy results is. Word2Vec algorithms are especially interesting because they allow us to perform arithmetic on the word vectors that yield both surprising and satisfying results. We call these “word analogies”. Some popular word analogies Word2Vec is capable of finding: “King” is to “Man” as “Queen” is to “Woman”. “France” is to “Paris” as “Italy” is to “Rome”. “December” is to “November” as “July” is to “June”. Not only can we cluster similar words together, we can make all these clusters have the same “structure”, all by using Word2Vec. Word2Vec was created by a team led by Tomas Mikolov at Google and has many advantages over earlier algorithms that attempt to do similar things, like Latent Semantic Analysis (LSA) or Latent Semantic Indexing (LSI). In this book we cover the GLoVe algorithm, which is an alternative to Word2Vec that both runs faster and yields superior results. It was invented by the guys at Stanford, who have created and published many NLP tools throughout the years that are now considered standard. I show you both their derivations in math, and how to implement them in code. We’ll do 3 different versions. The first version will show you how to solve the problem with vanilla gradient descent and Numpy. The second version will show you a simpler way of doing gradient descent using Theano’s automatic differentiation capabilities. The third version will make use of techniques found in recommender systems and matrix factorization. In fact, I devote an entire chapter to showing you how to use matrix factorization to recommend movies to users. We then take the main algorithm for solving matrix factorization problems, called alternating least squares, and apply it to solve GLoVe. Amazingly, all the technologies we discuss in this book can be downloaded and installed for FREE. That means all you need to invest after purchasing this book is your effort and your time. The only prerequisites are that you are comfortable with Python , Numpy, and Theano coding and you know the basics of deep learning. “Hold up... what’s deep learning and all this other crazy stuff you’re talking about?” If you are completely new to deep learning, you might want to check out my earlier books and courses on the subject, since they are required in order to understand this book: Deep Learning in Python https://www.udemy.com/data-science-de... Deep Learning in Python Prerequisities https://www.udemy.com/data-science-lo... Much like how IBM’s Deep Blue beat world champion chess player Garry Kasparov in 1996, Google’s AlphaGo recently made headlines when it beat world champion Lee Sedol in March 2016. What was amazing about this win was that experts in the field didn’t think it would happen for another 10 years. The search space of Go is much larger than that of chess, meaning that existing techniques for playing games with artificial intelligence were infeasible. Deep learning was the technique that enabled AlphaGo to correctly predict the outcome of its moves and defeat the world champion.

    Today, the best of A.I. has given us virtual assistants like Apple’s Siri and big data question/answering systems like IBM Watson. These statistical systems—based on Natural Language Processing—have accomplished a great deal. But, these assistants don’t really understand and do what we ask of them. They understand simple questions but cannot respond to complex or even slightly ambiguous ideas. Imagine you say, “I dropped my book and walked out of the kitchen to the bedroom. Where's the book?" A three-year old can grasp the meaning but your assistant can only scratch their virtual head. Brains aren’t what you think they are. They aren’t computers and they don’t process data. Cognitive science tells us that the brain is more of a pattern-matching machine than a processing machine. Understanding meaning—Natural Language Understanding—can’t be achieved through statistical processing. NLU relies on a richer environment that looks at patterns in linguistics, as well as sensory perceptions. Machine Intelligence, first published in 1998, takes the reader through the research that lead to Patom Theory, a brain-based theory based solely on a brain that stores, matches, and uses patterns. Ball, a cognitive scientist, began exploring the gap between how our brains interpret information and how computers work in 1983. Research, development collaborations and idea exchanges with the likes of A.I. co-founder and Turing Award winner Marvin Minsky became the foundation of Patom Theory. The theory has laid the groundwork work for NLU software developments that may lead to truly intelligent machines.

    One dumb human. The winner will define the future. “Laugh out loud funny!” “Thought-provoking” “A great read!” “Wry and witty”How fast can a relentlessly smart machine destroy a man’s life? It’s up to an average guy to represent the human race when a superintelligent robot arrives on the scene, ready to talk smack and inherit the world.TJ Marshall, a marketing exec at a leading robotics company, is driven over the edge by the world's most annoying machine, but he soon discovers the stakes are much higher than his own sanity.The Perfect is a fast-paced story about the near future bearing down on us, a future that will be scary for surprising reasons. Welcome to the contest of the incompetent human against artificial intelligence and information over-awareness. One world is about to get crushed.Funny, exciting, scary - techno satire with a strong dose of humor, mayhem and inspired lunacy. If you love your artificial intelligence with a knack for sarcasm, read The Perfect!

    Over the past fifty years, researchers have developed a series of quantitative models that are increasingly faithful to the biological architecture. Recently, deep learning convolution networks—which do not reflect several important features of the ventral stream architecture and physiology—have been trained with extremely large datasets, resulting in model neurons that mimic object recognition but do not explain the nature of the computations carried out in the ventral stream. This book develops a mathematical framework that describes learning of invariant representations of the ventral stream and is particularly relevant to deep convolutional learning networks.The authors propose a theory based on the hypothesis that the main computational goal of the ventral stream is to compute neural representations of images that are invariant to transformations commonly encountered in the visual environment and are learned from unsupervised experience. They describe a general theoretical framework of a computational theory of invariance (with details and proofs offered in appendixes) and then review the application of the theory to the feedforward path of the ventral stream in the primate visual cortex.