Skip to content

Latest commit

 

History

History
39 lines (33 loc) · 851 Bytes

syllabus.md

File metadata and controls

39 lines (33 loc) · 851 Bytes
layout title permalink
page
Syllabus
/syllabus/
<article class="post">

  <div class="entry">

The Course is divided into 2 parts,

Part I : Introduction to CNNs

  1. Introduction to Deep Learning and Computer Vision
  2. Feed Forward Neural Networks
  3. Introduction to CNNs
  4. Optimization for training Deep neural networks
  5. Deep Neural Networks
  6. Tricks for Improving the Learning

Part II : Advanced Topics in Deep Learning

  1. Introduction to DL packages/ Important architectures
  2. Visualizing CNNs
  3. Recurrent Neural Networks
  4. Generative Modelling using Deep networks
  5. Deep Reinforcement Learning
  6. Invited Talks from Researchers in Industry.