nn-part1 - Outline CS 464: Introduction to Machine Learning...

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CS 464: Introduction to Machine Learning Slides adapted from Chapter 4 Machine Learning by Tom M. Mitchell http://www-2.cs.cmu.edu/afs/cs.cmu.edu/user/mitchell/ftp/mlbook.html Outline • The Brain • Perceptrons • Gradient descent • Multi-layer networks • Backpropagation • Face recognition • Other terms/names connectionist parallel distributed processing neural computation adaptive networks. . • History 1943-McCulloch & Pitts are generally recognised as the designers of the first neural network 1949-First learning rule 1969-Minsky & Papert - perceptron limitation - Death of ANN 1980’s - Re-emergence of ANN - multi-layer networks • Cell structures Cell body Dendrites Axon Synaptic terminals The Brain • Ten billion (10 10 ) neurons • Neuron switching time > 0.1 msecs • Face Recognition ~0.1secs • On average, each neuron has several thousand connections • Hundreds of operations per second • High degree of parallel computation • Distributed representations • Die off frequently (never replaced) • Compensated for problems by massive parallelism Properties of Artificial &eural • Provide a general method for learning real-valued, discrete-valued, and vector-valued functions from examples • Many simple neuron-like threshold switching units
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nn-part1 - Outline CS 464: Introduction to Machine Learning...

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