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Deep Learning. John D. Kelleher

Deep-Learning.pdf
ISBN: 9780262537551 | 296 pages | 8 Mb

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

Free downloading books Deep Learning

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.

Deep Learning Tutorials — DeepLearning 0.1 documentation
Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer  Topic: deep-learning · GitHub
GitHub is where people build software. More than 40 million people use GitHub to discover, fork, and contribute to over 100 million projects. Deep learning - Wikipedia
Deep learning (also known as deep structured learning or hierarchical learning) is part of a broader family of machine learning methods based on artificial neural networks. Learning can be supervised, semi-supervised or unsupervised. Deep Learning - Scholarpedia
Deep Learning has revolutionised Pattern Recognition and Machine Learning. It is about credit assignment in adaptive systems with long  Deep Learning
Deep Learning is a new area of Machine Learning research, which has been introduced with the objective of moving Machine Learning closer to one of its  Deep Learning – Towards Data Science
Read writing about Deep Learning in Towards Data Science. Sharing concepts, ideas, and codes. Want to know how Deep Learning works? Here's a quick guide for
Once you've read this article, you will understand the basics of AI and ML. More importantly, you will understand how Deep Learning, the most  Introduction to Deep Learning | Coursera
Learn Introduction to Deep Learning from National Research University Higher School of Economics. The goal of this course is to give learners basic  Deep Learning in Computer Vision | Coursera
Learn Deep Learning in Computer Vision from National Research University Higher School of Economics. Deep learning added a huge boost to the already  Using neural nets to recognize handwritten digits - Neural networks
Neural networks approach the problem in a different way. The idea is to take a large number of handwritten digits, known as training examples, 

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