Deep Learning by John D. Kelleher

• Deep Learning
• John D. Kelleher
• Page: 296
• Format: pdf, ePub, mobi, fb2
• ISBN: 9780262537551
• Publisher: MIT Press

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English books pdf download Deep Learning (English Edition) by John D. Kelleher PDB 9780262537551

An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.

CS 229 - Deep Learning Cheatsheet
Neural networks are a class of models that are built with layers. Commonly used types of neural networks include convolutional and recurrent neural networks. Deep Learning Definition - Investopedia
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This Specialization will help you learn TensorFlow, a popular open-source framework for machine learning. Master this powerful tool for deep learning. Deep Learning (Neural Networks) — H2O 3.26.0.2 documentation
H2O's Deep Learning is based on a multi-layer feedforward artificial neural network that is trained with stochastic gradient descent using back-propagation. Deep Learning - MIT Technology Review
Intelligent Machines. Deep Learning. With massive amounts of computational power, machines can now recognize objects and translate  MIT 6.S191: Introduction to Deep Learning
6.S191: Introduction to Deep Learning. MIT's introductory course on deep learning methods and applications. Registration for 2019 is now open! Neural networks and deep learning
Neural networks and deep learning currently provide the best solutions to many problems in image recognition, speech recognition, and  deep-learning - Hacker Noon
Difference between Artificial Intelligence, Machine learning, and deep learning 10 Machine Learning, Data Science, and Deep Learning Courses for  What Is Deep Learning and How Will It Change Healthcare?
What makes deep learning different from other artificial intelligence strategies, and how will this innovative approach bring changes to the  K-12 Teaching and Learning - Hewlett Foundation
The students in this classroom are engaged in deep learning. They are drawing on knowledge and skills from many subject areas and experiences to build 

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