Neural Networks and Deep Learning

On successful completion of this course, students will have:a) Understand that current artificial neurons are simple abstractions of the biological neurons, realized as elements in a program or as circuits made of silicon.b) Recognize that current artificial neural networks, although yet to come close to having a fraction of the power of the human brain, can be trained to perform useful functions.c) Possess a good idea on diverse forms of artificial neural networks.d) Understand the underlying principles, structures and operations of different artificial neural networks.e) Supervised and Unsupervised learning. Design and select a suitable artificial neural network model for an application.f) Understand what artificial neural network can do for you. Appreciate successful applications in the areas of pattern classification, function approximation and time series prediction.

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