Author: Rocket Baby Club
Publisher: Rocket Baby Club
ISBN: 9781645164302
Category : Juvenile Nonfiction
Languages : en
Pages : 36
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Book Description
Eric the ladybug is an artist and traveler. He went to a mountain to watch the sunset and drew a painting of it. The next day when he woke up, he feels so thirsty and needs to find some water to drink. Will he be able to find the lowest point near him in order to find a water source? After an adventure with Eric the thirsty ladybug, you will know the most important intuition in machine learning, gradient descent.
Author: Jason Brownlee
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 266
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Book Description
Deep learning is the most interesting and powerful machine learning technique right now. Top deep learning libraries are available on the Python ecosystem like Theano and TensorFlow. Tap into their power in a few lines of code using Keras, the best-of-breed applied deep learning library. In this Ebook, learn exactly how to get started and apply deep learning to your own machine learning projects.
Author: Paolo Perrotta
Publisher: Pragmatic Bookshelf
ISBN: 1680507710
Category : Computers
Languages : en
Pages : 437
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Book Description
You've decided to tackle machine learning - because you're job hunting, embarking on a new project, or just think self-driving cars are cool. 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. Peel away the obscurities of machine learning, starting from scratch and going all the way to deep learning. Machine learning can be intimidating, with its reliance on math and algorithms that most programmers don't encounter in their regular work. Take a hands-on approach, writing the Python code yourself, without any libraries to obscure what's really going on. Iterate on your design, and add layers of complexity as you go. Build an image recognition application from scratch with supervised learning. Predict the future with linear regression. Dive into gradient descent, a fundamental algorithm that drives most of machine learning. Create perceptrons to classify data. Build neural networks to tackle more complex and sophisticated data sets. Train and refine those networks with backpropagation and batching. Layer the neural networks, eliminate overfitting, and add convolution to transform your neural network into a true deep learning system. Start from the beginning and code your way to machine learning mastery. What You Need: The examples in this book are written in Python, but don't worry if you don't know this language: you'll pick up all the Python you need very quickly. Apart from that, you'll only need your computer, and your code-adept brain.
Author: Eric LeMarque
Publisher:
ISBN: 9780553807653
Category : Athletes with disabilities
Languages : en
Pages : 0
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Book Description
In this gripping first-person account, former Olympian Eric LeMarque recounts a harrowing tale of survival—of eight days in the frozen wilderness, of losing his legs to frostbite, and coming face-to-face with death. But Eric’s ordeal on the mountain was only part of his struggle for survival—as he reveals, with startling candor, an even more harrowing and inspiring tale of fame and addiction, healing and triumph. On February 6, 2004, Eric, a former professional hockey player and expert snowboarder, set off for the top of 12,000-foot Mammoth Mountain in California’s vast Sierra Nevada mountain range. Wearing only a long-sleeve shirt, a thin wool hat, ski pants, and a lightweight jacket—and with only four pieces of gum for food—he soon found himself chest-high in snow, veering off the snowboard trail, and plunging into the wilderness. By nightfall he knew he was in a fight for his life…Surviving eight days in subfreezing temperatures, he would earn the name “The Miracle Man” by stunned National Guard Black Hawk Chopper rescuers. But Eric’s against-all-odds survival was no surprise to those who knew him. A gifted hockey player in his teens, he was later drafted by the Boston Bruins and a 1994 Olympian. But when his playing days were over, Eric felt adrift. Everything changed when he first tasted the rush of hard drugs—the highly addictive crystal meth—which filled a void left by hockey and fame. By the time Eric reached the peak of Mammoth Mountain in 2004, he was already dueling demons that had seized his soul. A riveting adventure, a brutal confessional, here Eric tells his remarkable story—his climb to success, his long and painful fall, and his ordeal in the wilderness. In the end, a man whose life had been based on athleticism would lose both his legs, relearn to walk—even snowboard—with prosthetics, and finally confront the ultimate test of survival: what it takes to find your way out of darkness, and—after so many lies—to tell truth… and begin to live again.
Author: Sean Gerrish
Publisher: MIT Press
ISBN: 0262537974
Category : Computers
Languages : en
Pages : 313
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Book Description
Everything you want to know about the breakthroughs in AI technology, machine learning, and deep learning—as seen in self-driving cars, Netflix recommendations, and more. The future is here: Self-driving cars are on the streets, an algorithm gives you movie and TV recommendations, IBM’s Watson triumphed on Jeopardy over puny human brains, computer programs can be trained to play Atari games. But how do all these things work? In this book, Sean Gerrish offers an engaging and accessible overview of the breakthroughs in artificial intelligence and machine learning that have made today’s machines so smart. Gerrish outlines some of the key ideas that enable intelligent machines to perceive and interact with the world. He describes the software architecture that allows self-driving cars to stay on the road and to navigate crowded urban environments; the million-dollar Netflix competition for a better recommendation engine (which had an unexpected ending); and how programmers trained computers to perform certain behaviors by offering them treats, as if they were training a dog. He explains how artificial neural networks enable computers to perceive the world—and to play Atari video games better than humans. He explains Watson’s famous victory on Jeopardy, and he looks at how computers play games, describing AlphaGo and Deep Blue, which beat reigning world champions at the strategy games of Go and chess. Computers have not yet mastered everything, however; Gerrish outlines the difficulties in creating intelligent agents that can successfully play video games like StarCraft that have evaded solution—at least for now. Gerrish weaves the stories behind these breakthroughs into the narrative, introducing readers to many of the researchers involved, and keeping technical details to a minimum. Science and technology buffs will find this book an essential guide to a future in which machines can outsmart people.
Author: Jason Brownlee
Publisher: Machine Learning Mastery
ISBN:
Category : Computers
Languages : en
Pages : 564
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Book Description
Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.
Author: Kevin Kelly
Publisher: Basic Books
ISBN: 078674703X
Category : Science
Languages : en
Pages : 528
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Book Description
Out of Control chronicles the dawn of a new era in which the machines and systems that drive our economy are so complex and autonomous as to be indistinguishable from living things.
Author: Jon Scieszka
Publisher: Simon and Schuster
ISBN: 1442444525
Category : Juvenile Fiction
Languages : en
Pages : 40
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Book Description
From the minds of Scieszka and Shannon comes a tale of a quixotic robot determined to conquer the earth. The only problem is that the earth he lands on is a suburban kitchen and he is three inches tall. Robot Zot, the fearless and unstoppable warrior, leaves a trail of destruction as he encounters blenders, toasters, and televisions. But when he discovers the princess...a pink cell phone...his mission takes a new course. Robot Zot must learn how to be a hero - in the name of true love.
Author: Matthew F. Dixon
Publisher: Springer Nature
ISBN: 3030410684
Category : Business & Economics
Languages : en
Pages : 565
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Book Description
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition to quants and data scientists in the field of quantitative finance. Machine Learning in Finance: From Theory to Practice is divided into three parts, each part covering theory and applications. The first presents supervised learning for cross-sectional data from both a Bayesian and frequentist perspective. The more advanced material places a firm emphasis on neural networks, including deep learning, as well as Gaussian processes, with examples in investment management and derivative modeling. The second part presents supervised learning for time series data, arguably the most common data type used in finance with examples in trading, stochastic volatility and fixed income modeling. Finally, the third part presents reinforcement learning and its applications in trading, investment and wealth management. Python code examples are provided to support the readers' understanding of the methodologies and applications. The book also includes more than 80 mathematical and programming exercises, with worked solutions available to instructors. As a bridge to research in this emergent field, the final chapter presents the frontiers of machine learning in finance from a researcher's perspective, highlighting how many well-known concepts in statistical physics are likely to emerge as important methodologies for machine learning in finance.
Author: Jenny Odell
Publisher: Melville House
ISBN: 1612198554
Category : Technology & Engineering
Languages : en
Pages : 259
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Book Description
** A New York Times Bestseller ** NAMED ONE OF THE BEST BOOKS OF THE YEAR BY: Time • The New Yorker • NPR • GQ • Elle • Vulture • Fortune • Boing Boing • The Irish Times • The New York Public Library • The Brooklyn Public Library "A complex, smart and ambitious book that at first reads like a self-help manual, then blossoms into a wide-ranging political manifesto."—Jonah Engel Bromwich, The New York Times Book Review One of President Barack Obama's "Favorite Books of 2019" Porchlight's Personal Development & Human Behavior Book of the Year In a world where addictive technology is designed to buy and sell our attention, and our value is determined by our 24/7 data productivity, it can seem impossible to escape. But in this inspiring field guide to dropping out of the attention economy, artist and critic Jenny Odell shows us how we can still win back our lives. Odell sees our attention as the most precious—and overdrawn—resource we have. And we must actively and continuously choose how we use it. We might not spend it on things that capitalism has deemed important … but once we can start paying a new kind of attention, she writes, we can undertake bolder forms of political action, reimagine humankind’s role in the environment, and arrive at more meaningful understandings of happiness and progress. Far from the simple anti-technology screed, or the back-to-nature meditation we read so often, How to do Nothing is an action plan for thinking outside of capitalist narratives of efficiency and techno-determinism. Provocative, timely, and utterly persuasive, this book will change how you see your place in our world.
