Lecture Notes || SNS Courseware

Subject Details

Dept : AIDS

Sem : 6

Regul : 2019

Faculty : Gulshan Banu

phone : 9655507259

E-mail : gulshan.a.ad@snsce.ac.in

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Lecture Notes

UNIT 1:

Introduction to machine learning

Linear models (SVMs and Perceptrons)

What a shallow network computes

Training a network: loss functions

Neural networks as universal function approximates.

UNIT 2:

History of Deep Learning

Back propagation and regularization

Batch normalization

Convolutional Networks

Generative Adversarial Networks (GAN)

VC Dimension and Neural Nets

UNIT 3:

Auto encoders

Linear (PCA, LDA) and manifolds, metric learning

Introduction to Convnet

VGG, Inception, ResNet

Training a Convnet

weights initialization, batch normalization, hyperparameter optimization.

UNIT 4:

Optimization in deep learning

Non-convex optimization for deep networks

Spatial Transformer Networks

Recurrent networks, LSTM

Recurrent Neural Network Language Models

Deep Reinforcement Learning

Computational & Artificial Neuroscience

UNIT 5:

Imagenet

Detection

Natural Language Processing Word2Vec

Joint Detection

Face Recognition

Scene Understanding

Gathering Image Captions.

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