Machine learning - Wikipedia, the free encyclopedia Machine learning is a subfield of computer science and statistics that deals with the construction and study of systems that can learn from data, rather than follow only explicitly programmed instructions. Besides CS and Statistics, it has strong ties to
Deep learning - Wikipedia, the free encyclopedia Deep learning (deep structured learning or hierarchical learning) is a set of algorithms in machine learning that attempt to model high-level abstractions in data by using model architectures composed of multiple non-linear transformations.[1](p198)[2][3]
The Next Generation of Neural Networks - YouTube Google Tech Talks November, 29 2007 In the 1980's, new learning algorithms for neural networks promised to solve difficult classification tasks, like speech or object recognition, by learning many layers of non-linear features. The results were disappoint
Boltzmann machine - Scholarpedia A Boltzmann machine is a network of symmetrically connected, neuron-like units that make stochastic decisions about whether to be on or off. Boltzmann machines have a simple learning algorithm (Hinton & Sejnowski, 1983) that allows them to discover intere
Deep learning - Upload, Share, and Discover Content on SlideShare 機械学習×プログラミング勉強会 vol.2 http://atnd.org/events/33182 で発表した資料 ... Transcript 1. Deep Learning 株式会社ウサギィ 五木田 和也 2012/11/0912年11月9日金曜日 2.
Restricted Boltzmann Machines (RBM) ¶ - Deep Learning Restricted Boltzmann Machines (RBM) Boltzmann Machines (BMs) are a particular form of log-linear Markov Random Field (MRF), i.e., for which the energy function is linear in its free parameters. To make them powerful enough to represent complicated ...
Recent Developments in Deep Learning - YouTube Google Tech Talk March 19, 2010 ABSTRACT Presented by Geoff Hinton, University of Toronto. Deep networks can be learned efficiently from unlabeled data. The layers of representation are learned one at a time using a simple learning module that has only on
Nitish Srivastava - Department of Computer Science, University of Toronto Nitish Srivastava PhD student Machine Learning Group Department of Computer Science University of Toronto About Me I am a PhD student in the Machine Learning Group working with Geoffrey Hinton and Ruslan Salakhutdinov. I obtained my Bachelor's in ...
UFLDL Recommended Readings - Ufldl - Deep Learning If you're learning about UFLDL (Unsupervised Feature Learning and Deep Learning), here is a list of papers to consider reading. We're assuming you're already familiar with basic machine learning at the level of [CS229 (lecture notes available)]. The basic
Home Page of Geoffrey Hinton - Department of Computer Science, University of Toronto Check out the new web page for Machine Learning at Toronto Information for prospective students: I will not be taking any more graduate students, visiting students, summer students or visitors, so please do not apply to work with me. News Results of the 2