Deep_Learning

Week 1

Basics of Soft Computing(Neural Networks) to Building your First Neural Network

• Introduction To Artificial Neural Networks(ANN) -

  • Watch the Introductory Videos To Neural Networks here and read Part 1 of the Deep Learning Book. here. Download the Full Book from here if you wish to.
  • To see Artificial Neural Networks in Action, view the Ipython Notebook here and Blog post here

• Multi-Layer Perceptron Model and McCulloch-Pitts Neuron

  • Read this Blog Post here and Watch this video by Daniel Shiffmann right here. Also read about McCulloch-Pitts Neuron here
  • View The Jupyter Notebook on the usage of MLP on kaggle's MNIST dataset here

• Building a Neural Network

  • Build a Neural Network in 4 minutes by Siraj Raval
  • Type out the neural network code yourself in a text editor, compile, and run it locally (using no ML libraries)

Week 2

Forward Propagation, BackPropagation and Regularization.

• Read the Forward Propagation Blogpost. You will Find its application as well in this Jupyter Notebook.

• Read the Gradient Descent Blogpost. Watch Backpropagation in 5 minutes by Siraj Raval.

• Read about Regularization. A complete tutorial on Lasso and Ridge Regularization along with code in python.

• Optimization

  • Read about optimization. Explore the common Deep Learning Optimization Algorithms like:- SGD, Mini Batch SGD, Momentum, Adagrad, RMSProp, Adadelta, Adam.

Week 3

Convolutional Neural Networks

• Watch the Convolutional Networks Specialization on Coursera, found here.
• Read A Beginner's Guide to Convolutional Neural Networks- part 1 and A Beginner's Guide to Convolutional Neural Network part 2 By Adit Deshpande.
• Watch Siraj Raval's Video on CNN here and here.
• Read module 2 by Andrej Karpathy in CS231n here
• Write out a simple CNN yourself (using no ML libraries). You can use this post for reference.
• Read The 9 Deep Learning papers you Need to know to Understand CNNs by Adit Deshpande.

Week 4

Recurrent Neural Networks

• Watch the Sequence Models Specialization on Coursera, found here.
• Read The blogpost on Anyone can Learn to code an RNN BY Andrew Trask.
• Read the Blogpost on LSTMs By Christopher Olah.
• Read Andrej Karpathy's Blogpost on RNNs for a Deeper Understanding.
• Write out a simple RNN yourself (using no ML libraries).

Week 5

Deep Learning Tools

• Watch CS20 (Tensorflow for DL research). Slides are here. Playlist is here
• Learn which GPU provider is best for you here
• Watch Install CPU and GPU version of Tensorflow on Windows by Sentdex and also Installing The GPU version of tensorflow to make use of your cuda GPU by Sentdex.
• Watch the introduction to tensorflow playlist here
• Read Keras Example code to quickly understand its structure here
• Getting started with Pytorch Tutorials. Build an image classifier in Pytorch

Week 6

Unsupervised Deep Learning

• Read the Introduction To Unsupervised Deep Learning by Analytics Vidhya.
• Read this material by Carnegie Mellon University.
• Read this Blogpost on Auto Encoders by Stanford.edu. Watch this video on AutoEncoders by Siraj Raval.
• Read my Blogpost on Boltzmann Machines and Restricted Boltzmann Machines
• Build an Autoencoder using Keras. Use This Repository
• Read This Blog Post on Self Taught Learning By Stanford edu.

Week 7

Generative Adversarial Networks

• Read the blogpost on A beginner's Guide to Generative Adversarial Networks by skymind.ai
• Try this Blogpost for an edge.
• Read the NeurIPS 2016 tutorial on GANs.
• View this notebook on Deep Convoultional GANs to Generate images of Handwritten digits using Tensorflow.(Credits to Tensorflow)
• See more on GAN application in the Papers with code website. There are several papers on Different GAN applications whose results you can replicate.

Week 8

Deep Reinforcement Learning

• Read A beginner's Introduction For Deep Reinforcement Learning to know the basics.
• Read my Blogpost on Q-learning:- pLaying Open AI's Taxi Version-2 to see a first Hand application of DRL
• Watch CS-294 here
• Build a Deep Q Network using Tensorflow
• Read my Blogpost on DeepMind's AlphaGo Zero: Explanation

A list of few Books and Materials, just for reference.