DEEP LEARNING COURSE

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INTRODUCTION

    • Intro to TensorFlow
    • Computational Graph
    • Key highlights
    • Creating a Graph
    • Regression example
    • Gradient Descent
    • TensorBoard
    • Modularity
    • Sharing Variables
    • Keras

PERCEPTRONS

    • What is a Perceptron
    • XOR Gate

ACTIVATION FUNCTIONS

    • Sigmoid
    • ReLU
    • Hyperbolic Fns
    • Softmax

ARTIFICIAL NEURAL NETWORKS

    • Introduction
    • Perceptron Training Rule
    • Gradient Descent Rule

GRADIENT DESCENT AND BACKPROPAGATION

    • Gradient Descent
    • Stochastic Gradient Descent
    • Backpropagation
    • Some problems in ANN

OPTIMIZATION AND REGULARIZATION

    • Overfitting and Capacity
    • Cross Validation
    • Feature Selection
    • Regularization
    • Hyperparameters

INTRO TO CONVOLUTIONAL NEURAL NETWORKS

    • Intro to CNNs
    • Kernel filter
    • Principles behind CNNs
    • Multiple Filters
    • CNN applications

INTRO TO RECURRENT NEURAL NETWORKS

    • Intro to RNNs
    • Unfolded RNNs
    • Seq2Seq RNNs
    • LSTM
    • RNN applications

DEEP LEARNING APPLICATIONS

    • Image Processing
    • Natural Language Processing
    • Speech Recognition
    • Video Analytics

CONTACT US

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