Lecture Notes || SNS Courseware

Subject Details

Dept : CSE

Sem : 6

Regul : 2019

Faculty : Ramesh kalyan G

phone : NIL

E-mail : ramesh.g.cse@snsct.org

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Lecture Notes

UNIT 1:

Basic Concept of Neurons

Perceptron Algorithm

Single Layer Neural Network

Multilayer Neural Network

Feed Forward Neural Network

Back propagation Networks

Create and deploy neural networks using Tensor Flow for Image data

UNIT 2:

Deep Neural Networks

Gradient Descent

Vanishing Gradient Problem

Deep Neural Networks

Differentiation Algorithms

Heuristics for Faster Training

UNIT 3:

Activation Function

CNN Architectures

Deep Recurrent Networks

Create and deploy Convolutional Neural networks using Keras for Image data.

Pooling Layers Hyper parameter

Recurrent Neural Networks

UNIT 4:

Autoencoders

Long Short Term Memory (LSTM) Networks

Sequence Prediction, Gated Recurrent

Variational Autoencoders

UNIT 5:

Attention models for Computer Vision

Automatic Image Captioning

Image generation with Generative adversarial networks

Images segmentation

Object Detection

Video to Text with LSTM models

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