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Wide N Deep
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Book Synopsis Proceedings of the 1st Workshop on Deep Learning for Recommender Systems by : Alexandros Karatzoglou
Download or read book Proceedings of the 1st Workshop on Deep Learning for Recommender Systems written by Alexandros Karatzoglou and published by . This book was released on 2016-09-15 with total page 47 pages. Available in PDF, EPUB and Kindle. Book excerpt: Workshop on Deep Learning for Recommender Systems Sep 15, 2016-Sep 15, 2016 Boston, USA. You can view more information about this proceeding and all of ACM�s other published conference proceedings from the ACM Digital Library: http://www.acm.org/dl.
Download or read book Deep and Wide written by Andy Stanley and published by Zondervan. This book was released on 2016-02-09 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Create a church unchurched people absolutely love to attend. Deep and Wide provides church leaders with an in-depth look into North Point Community Church and its strategy for creating churches unchurched people absolutely love to attend. Now available in an expanded edition, this trusted resource has sold over 250,000 copies. In it, Andy Stanley explains: His strategy for preaching and programming to both mature believers and cynical unbelievers North Point's spiritual formation model: The Five Faith Catalysts Three essential ingredients for creating irresistible environments How to tackle the challenge of transitioning a local congregation If your team is more concerned with who you are reaching than who you are keeping, the expanded edition of Deep and Wide will be more than a book you read; it will be a resource you come back to over and over! New bonus content includes a study guide, church staff helps, and an interview with Andy on the most frequently asked questions about Deep and Wide.
Book Synopsis Wisdom Wide and Deep by : Shaila Catherine
Download or read book Wisdom Wide and Deep written by Shaila Catherine and published by Simon and Schuster. This book was released on 2011-10-10 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wisdom Wide and Deep is a comprehensive guide to an in-depth training that emphasizes the application of concentrated attention (jhana) to profound and liberating insight (vipassana). With calm, tranquility, and composure established through a practical experience of jhana meditators are able to halt the seemingly endless battle against hindrances, eliminate distraction, and facilitate a penetrative insight into the subtle nature of matter and mind. It was for this reason the Buddha frequently exhorted his students, Wisdom Wide and Deep follows and amplifies the teachings in Shaila Catherine's acclaimed first book, Focused and Fearless: A Meditator's Guide to States of Deep Joy, Calm, and Clarity. Readers will learn to develop this profound stability, sustain an in-depth examination of the nuances of mind and matter, and ultimately unravel deeply conditioned patterns that perpetuate suffering. This fully detailed manual for the mind sure to become a trusted companion to many inner explorers.
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.
Book Synopsis Deep Learning with TensorFlow by : Giancarlo Zaccone
Download or read book Deep Learning with TensorFlow written by Giancarlo Zaccone and published by Packt Publishing Ltd. This book was released on 2017-04-24 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide About This Book Learn how to implement advanced techniques in deep learning with Google's brainchild, TensorFlow Explore deep neural networks and layers of data abstraction with the help of this comprehensive guide Real-world contextualization through some deep learning problems concerning research and application Who This Book Is For The book is intended for a general audience of people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will Learn Learn about machine learning landscapes along with the historical development and progress of deep learning Learn about deep machine intelligence and GPU computing with the latest TensorFlow 1.x Access public datasets and utilize them using TensorFlow to load, process, and transform data Use TensorFlow on real-world datasets, including images, text, and more Learn how to evaluate the performance of your deep learning models Using deep learning for scalable object detection and mobile computing Train machines quickly to learn from data by exploring reinforcement learning techniques Explore active areas of deep learning research and applications In Detail Deep learning is the step that comes after machine learning, and has more advanced implementations. Machine learning is not just for academics anymore, but is becoming a mainstream practice through wide adoption, and deep learning has taken the front seat. As a data scientist, if you want to explore data abstraction layers, this book will be your guide. This book shows how this can be exploited in the real world with complex raw data using TensorFlow 1.x. Throughout the book, you'll learn how to implement deep learning algorithms for machine learning systems and integrate them into your product offerings, including search, image recognition, and language processing. Additionally, you'll learn how to analyze and improve the performance of deep learning models. This can be done by comparing algorithms against benchmarks, along with machine intelligence, to learn from the information and determine ideal behaviors within a specific context. After finishing the book, you will be familiar with machine learning techniques, in particular the use of TensorFlow for deep learning, and will be ready to apply your knowledge to research or commercial projects. Style and approach This step-by-step guide will explore common, and not so common, deep neural networks and show how these can be exploited in the real world with complex raw data. With the help of practical examples, you will learn how to implement different types of neural nets to build smart applications related to text, speech, and image data processing.
Book Synopsis A Hunger So Wide and So Deep by : Becky W. Thompson
Download or read book A Hunger So Wide and So Deep written by Becky W. Thompson and published by U of Minnesota Press. This book was released on 1994 with total page 180 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first of its kind, A Hunger So Wide and So Deep challenges the popular notion that eating problems occur only among white, well-to-do, heterosexual women. Becky W. Thompson shows us how race, class, sexuality, and nationality can shape women's eating problems. Based on in-depth life history interviews with African-American, Latina, and lesbian women, her book chronicles the effects of racism, poverty, sexism, acculturation, and sexual abuse on women's bodies and eating patterns. A Hunger So Wide and So Deep dispels popular stereotypes of anorexia and bulimia as symptoms of vanity and underscores the risks of mislabeling what is often a way of coping with society's own disorders. By featuring the creative ways in which women have changed their unwanted eating patterns and regained trust in their bodies and appetites, Thompson offers a message of hope and empowerment that applies across race, class, and sexual preference.
Book Synopsis Efficient Processing of Deep Neural Networks by : Vivienne Sze
Download or read book Efficient Processing of Deep Neural Networks written by Vivienne Sze and published by Springer Nature. This book was released on 2022-05-31 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a structured treatment of the key principles and techniques for enabling efficient processing of deep neural networks (DNNs). DNNs are currently widely used for many artificial intelligence (AI) applications, including computer vision, speech recognition, and robotics. While DNNs deliver state-of-the-art accuracy on many AI tasks, it comes at the cost of high computational complexity. Therefore, techniques that enable efficient processing of deep neural networks to improve key metrics—such as energy-efficiency, throughput, and latency—without sacrificing accuracy or increasing hardware costs are critical to enabling the wide deployment of DNNs in AI systems. The book includes background on DNN processing; a description and taxonomy of hardware architectural approaches for designing DNN accelerators; key metrics for evaluating and comparing different designs; features of DNN processing that are amenable to hardware/algorithm co-design to improve energy efficiency and throughput; and opportunities for applying new technologies. Readers will find a structured introduction to the field as well as formalization and organization of key concepts from contemporary work that provide insights that may spark new ideas.
Book Synopsis The Principles of Deep Learning Theory by : Daniel A. Roberts
Download or read book The Principles of Deep Learning Theory written by Daniel A. Roberts and published by Cambridge University Press. This book was released on 2022-05-26 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume develops an effective theory approach to understanding deep neural networks of practical relevance.
Book Synopsis Deep Learning for Robot Perception and Cognition by : Alexandros Iosifidis
Download or read book Deep Learning for Robot Perception and Cognition written by Alexandros Iosifidis and published by Academic Press. This book was released on 2022-02-04 with total page 638 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks. - Presents deep learning principles and methodologies - Explains the principles of applying end-to-end learning in robotics applications - Presents how to design and train deep learning models - Shows how to apply deep learning in robot vision tasks such as object recognition, image classification, video analysis, and more - Uses robotic simulation environments for training deep learning models - Applies deep learning methods for different tasks ranging from planning and navigation to biosignal analysis
Book Synopsis The Night Is Deep and Wide by : Gillian Sze
Download or read book The Night Is Deep and Wide written by Gillian Sze and published by Orca Book Publishers. This book was released on 2021-03-16 with total page 23 pages. Available in PDF, EPUB and Kindle. Book excerpt: ★ “A lovely visual lullaby to soothe youngest readers to sleep.”—Publishers Weekly, starred review Rich imagery, gentle rhythm and soothing repetition will lull your little one to sleep as the tulips close for the night, one by one. In this bedtime story written as an Italian villanelle, poet Gillian Sze makes use of the poetic forms of cyclic pattern and rhyme scheme to create a melodious lullaby. A young child comes in from picking flowers as the creatures around their home all settle down for the evening. Songbirds curl against their mothers’ sides, the house slumps and sighs low, a hush settles as times slows. And little readers are invited to rest their heads and be soothed to sleep as moonlight falls on eyes that close.
Book Synopsis Learning Deep Architectures for AI by : Yoshua Bengio
Download or read book Learning Deep Architectures for AI written by Yoshua Bengio and published by Now Publishers Inc. This book was released on 2009 with total page 145 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theoretical results suggest that in order to learn the kind of complicated functions that can represent high-level abstractions (e.g. in vision, language, and other AI-level tasks), one may need deep architectures. Deep architectures are composed of multiple levels of non-linear operations, such as in neural nets with many hidden layers or in complicated propositional formulae re-using many sub-formulae. Searching the parameter space of deep architectures is a difficult task, but learning algorithms such as those for Deep Belief Networks have recently been proposed to tackle this problem with notable success, beating the state-of-the-art in certain areas. This paper discusses the motivations and principles regarding learning algorithms for deep architectures, in particular those exploiting as building blocks unsupervised learning of single-layer models such as Restricted Boltzmann Machines, used to construct deeper models such as Deep Belief Networks.
Book Synopsis The Deep, Wide, and Dark by : Dewey D. White
Download or read book The Deep, Wide, and Dark written by Dewey D. White and published by Xlibris Corporation. This book was released on 2011-12-27 with total page 208 pages. Available in PDF, EPUB and Kindle. Book excerpt: Venture into the blackness of space with Dewey D. Whites well-wrought The Deep, Wide, and Dark. The science is nothing short of sorcery as an extra-terrestrial humanoid named John Jay Corsey gives mankind a dimensional boost from Einsteins quantum theory for the love of a twenty-year-old stripper. With science heretofore unknown to humans but which was found to be related to the alien spacecraft that crash-landed near Roswell, New Mexico, Corsey becomes the center of a massive project to build the first faster than light starship to take flight into universa incognita searching for two unearthly elements, but quickly more than rocks are found by the newly-minted Space Marine Corps. Corsey found mankind (specifically the U.S. government) unprepared but willing to build the machine. They jumped right in to the project with the verve and gusto typical of modern man: cobbling together human and extra-terrestrial science to make it a shining reality. On a fenced-in, 200 sq. mile swath of Arizona-New Mexico desert, Sol Base One is built. The nascent masters of the deep, wide, and dark universal empyrean, the Space Marines Corps recruits the best minds and bodies to man the Terrain Explorer, the first starship in human history. The rush to build it becomes a race as world politics views it as an unwise decision and prepares to stymie the ships launch after the Space Marines crafty commandant refuses to reveals the program and its intentions. The next decision made is to launch the mission (425 men on board the Terrain Explorer) before the U.N. could send in inspection teams. And thus, the fate of humanitys first venture into the stars is sealed. Join Capt. Jackson Edison Jed Devlon and the crew of the Terrain Explorer in what promises to be a thrilling, masterful exploration of the possibilities of time and space. Will they land on earth-like worlds such as humanity knows, therefore solidifying the fact of infinite replication in the universe? Who, amongst the extra-terrestrial races will they meet and who will be their friend or enemy? How will they survive? The permutations grip readers with excitement. The writing is riveting in detail and shines with crystal-clear believability. The future is at stake
Download or read book Deep Learning written by Michael Fullan and published by Corwin Press. This book was released on 2017-11-06 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: New Pedagogies for Deep Learning (NDPL) provides a comprehensive strategy for systemwide transformation. Using the 6 competencies of NDPL and a wealth of vivid examples, Fullan re-defines and re-examines what deep learning is and identifies the practical strategies for revolutionizing learning and leadership.
Book Synopsis Deep Learning with Keras by : Antonio Gulli
Download or read book Deep Learning with Keras written by Antonio Gulli and published by Packt Publishing Ltd. This book was released on 2017-04-26 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with the basics of Keras to implement fast and efficient deep-learning models About This Book Implement various deep-learning algorithms in Keras and see how deep-learning can be used in games See how various deep-learning models and practical use-cases can be implemented using Keras A practical, hands-on guide with real-world examples to give you a strong foundation in Keras Who This Book Is For If you are a data scientist with experience in machine learning or an AI programmer with some exposure to neural networks, you will find this book a useful entry point to deep-learning with Keras. A knowledge of Python is required for this book. What You Will Learn Optimize step-by-step functions on a large neural network using the Backpropagation Algorithm Fine-tune a neural network to improve the quality of results Use deep learning for image and audio processing Use Recursive Neural Tensor Networks (RNTNs) to outperform standard word embedding in special cases Identify problems for which Recurrent Neural Network (RNN) solutions are suitable Explore the process required to implement Autoencoders Evolve a deep neural network using reinforcement learning In Detail This book starts by introducing you to supervised learning algorithms such as simple linear regression, the classical multilayer perceptron and more sophisticated deep convolutional networks. You will also explore image processing with recognition of hand written digit images, classification of images into different categories, and advanced objects recognition with related image annotations. An example of identification of salient points for face detection is also provided. Next you will be introduced to Recurrent Networks, which are optimized for processing sequence data such as text, audio or time series. Following that, you will learn about unsupervised learning algorithms such as Autoencoders and the very popular Generative Adversarial Networks (GAN). You will also explore non-traditional uses of neural networks as Style Transfer. Finally, you will look at Reinforcement Learning and its application to AI game playing, another popular direction of research and application of neural networks. Style and approach This book is an easy-to-follow guide full of examples and real-world applications to help you gain an in-depth understanding of Keras. This book will showcase more than twenty working Deep Neural Networks coded in Python using Keras.
Book Synopsis Deep Learning and the Game of Go by : Kevin Ferguson
Download or read book Deep Learning and the Game of Go written by Kevin Ferguson and published by Simon and Schuster. This book was released on 2019-01-06 with total page 611 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game. Foreword by Thore Graepel, DeepMind Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning-based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot! About the Book Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you'll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You'll enjoy watching your bot master the game of Go, and along the way, you'll discover how to apply your new deep learning skills to a wide range of other scenarios! What's inside Build and teach a self-improving game AI Enhance classical game AI systems with deep learning Implement neural networks for deep learning About the Reader All you need are basic Python skills and high school-level math. No deep learning experience required. About the Author Max Pumperla and Kevin Ferguson are experienced deep learning specialists skilled in distributed systems and data science. Together, Max and Kevin built the open source bot BetaGo. Table of Contents PART 1 - FOUNDATIONS Toward deep learning: a machine-learning introduction Go as a machine-learning problem Implementing your first Go bot PART 2 - MACHINE LEARNING AND GAME AI Playing games with tree search Getting started with neural networks Designing a neural network for Go data Learning from data: a deep-learning bot Deploying bots in the wild Learning by practice: reinforcement learning Reinforcement learning with policy gradients Reinforcement learning with value methods Reinforcement learning with actor-critic methods PART 3 - GREATER THAN THE SUM OF ITS PARTS AlphaGo: Bringing it all together AlphaGo Zero: Integrating tree search with reinforcement learning
Book Synopsis Dive Into Deep Learning by : Joanne Quinn
Download or read book Dive Into Deep Learning written by Joanne Quinn and published by Corwin Press. This book was released on 2019-07-15 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: The leading experts in system change and learning, with their school-based partners around the world, have created this essential companion to their runaway best-seller, Deep Learning: Engage the World Change the World. This hands-on guide provides a roadmap for building capacity in teachers, schools, districts, and systems to design deep learning, measure progress, and assess conditions needed to activate and sustain innovation. Dive Into Deep Learning: Tools for Engagement is rich with resources educators need to construct and drive meaningful deep learning experiences in order to develop the kind of mindset and know-how that is crucial to becoming a problem-solving change agent in our global society. Designed in full color, this easy-to-use guide is loaded with tools, tips, protocols, and real-world examples. It includes: • A framework for deep learning that provides a pathway to develop the six global competencies needed to flourish in a complex world — character, citizenship, collaboration, communication, creativity, and critical thinking. • Learning progressions to help educators analyze student work and measure progress. • Learning design rubrics, templates and examples for incorporating the four elements of learning design: learning partnerships, pedagogical practices, learning environments, and leveraging digital. • Conditions rubrics, teacher self-assessment tools, and planning guides to help educators build, mobilize, and sustain deep learning in schools and districts. Learn about, improve, and expand your world of learning. Put the joy back into learning for students and adults alike. Dive into deep learning to create learning experiences that give purpose, unleash student potential, and transform not only learning, but life itself.
Download or read book Deep Learning written by Li Deng and published by . This book was released on 2014 with total page 212 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an overview of general deep learning methodology and its applications to a variety of signal and information processing tasks
