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2. Bayesian Learning

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3. Discriminant Function

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4. Linear Classifier

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5. Support Vector, Linear Machine and Multi class Support Vector Machines

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6. Optimisation and Non Linear Function

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7. Neural Network and Multi layer Perceptron

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8. Back Propagation Learning and Loss function

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9. Autoencoder, PCA , Autoencoder training and Autoencoder variants

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