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Fdp on machine learning

Course Contents:

Introduction to Machine learning,Classification and Regression Problems

Non parametric density estimation and classification – Parzen Window, Nearest Neighbours

Dimensionality Reduction, PCA, FLD, Perceptron

Unsupervised Classification (K-Means, fuzzy C means Clustering), Clustering using Neural Network (SOM)

Need for Deep Learning, Potential/Successful Applications

Mathematical background on Convolutional Neural Networks

Mathematical background on Restricted Boltzmann Machine and Deep Belief Networks

Hands on sessions using the Machine learning tools.

 

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