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Deep Learning
  • Language: en
  • Pages: 800

Deep Learning

  • Type: Book
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  • Published: 2016-11-18
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  • Publisher: MIT Press

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.

Deep Learning
  • Language: en
  • Pages: 800

Deep Learning

  • Type: Book
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  • Published: 2016-11-10
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  • Publisher: MIT Press

"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...

Perturbations, Optimization, and Statistics
  • Language: en
  • Pages: 412

Perturbations, Optimization, and Statistics

  • Type: Book
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  • Published: 2017-09-22
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  • Publisher: MIT Press

In nearly all machine learning, decisions must be made given current knowledge. Surprisingly, making what is believed to be the best decision is not always the best strategy, even when learning in a supervised learning setting. An emerging body of work on learning under different rules applies perturbations to decision and learning procedures. These methods provide simple and highly efficient learning rules with improved theoretical guarantees. This book describes perturbation-based methods developed in machine learning to augment novel optimization methods with strong statistical guarantees, offering readers a state-of-the-art overview. Chapters address recent modeling ideas that have arise...

Zones of Control
  • Language: en
  • Pages: 848

Zones of Control

  • Type: Book
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  • Published: 2016-05-06
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  • Publisher: MIT Press

Examinations of wargaming for entertainment, education, and military planning, in terms of design, critical analysis, and historical contexts.

Information Theory, Inference and Learning Algorithms
  • Language: en
  • Pages: 628

Information Theory, Inference and Learning Algorithms

Fun and exciting textbook on the mathematics underpinning the most dynamic areas of modern science and engineering.

Architects of Intelligence
  • Language: en
  • Pages: 554

Architects of Intelligence

Book Description How will AI evolve and what major innovations are on the horizon? What will its impact be on the job market, economy, and society? What is the path toward human-level machine intelligence? What should we be concerned about as artificial intelligence advances? Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community. Martin has wide-ranging conversations with twenty-three of the world's foremost researchers and entrepreneurs working in AI and robotics: Demis Hassabis (DeepMind), Ray Kur...

Introduction to Artificial Intelligence
  • Language: en
  • Pages: 356

Introduction to Artificial Intelligence

  • Type: Book
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  • Published: 2018-01-18
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  • Publisher: Springer

This accessible and engaging textbook presents a concise introduction to the exciting field of artificial intelligence (AI). The broad-ranging discussion covers the key subdisciplines within the field, describing practical algorithms and concrete applications in the areas of agents, logic, search, reasoning under uncertainty, machine learning, neural networks, and reinforcement learning. Fully revised and updated, this much-anticipated second edition also includes new material on deep learning. Topics and features: presents an application-focused and hands-on approach to learning, with supplementary teaching resources provided at an associated website; contains numerous study exercises and s...

Neural Smithing
  • Language: en
  • Pages: 346

Neural Smithing

  • Type: Book
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  • Published: 1999-02-17
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  • Publisher: MIT Press

Artificial neural networks are nonlinear mapping systems whose structure is loosely based on principles observed in the nervous systems of humans and animals. The basic idea is that massive systems of simple units linked together in appropriate ways can generate many complex and interesting behaviors. This book focuses on the subset of feedforward artificial neural networks called multilayer perceptrons (MLP). These are the mostly widely used neural networks, with applications as diverse as finance (forecasting), manufacturing (process control), and science (speech and image recognition).This book presents an extensive and practical overview of almost every aspect of MLP methodology, progressing from an initial discussion of what MLPs are and how they might be used to an in-depth examination of technical factors affecting performance. The book can be used as a tool kit by readers interested in applying networks to specific problems, yet it also presents theory and references outlining the last ten years of MLP research.

Introduction to Machine Learning
  • Language: en
  • Pages: 640

Introduction to Machine Learning

  • Type: Book
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  • Published: 2014-08-29
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  • Publisher: MIT Press

The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis...

Deep Learning. Das umfassende Handbuch
  • Language: de
  • Pages: 912

Deep Learning. Das umfassende Handbuch

• Mathematische Grundlagen für Machine und Deep Learning • Umfassende Behandlung zeitgemäßer Verfahren: tiefe Feedforward-Netze, Regularisierung, Performance-Optimierung sowie CNNs, Rekurrente und Rekursive Neuronale Netze • Zukunftsweisende Deep-Learning-Ansätze sowie von Ian Goodfellow neu entwickelte Konzepte wie Generative Adversarial Networks Deep Learning ist ein Teilbereich des Machine Learnings und versetzt Computer in die Lage, aus Erfahrungen zu lernen. Dieses Buch behandelt umfassend alle Aspekte, die für den Einsatz und die Anwendung von Deep Learning eine Rolle spielen: In Teil I erläutern die Autoren die mathematischen Grundlagen für Künstliche Intelligenz, Neuron...