deepnetworks

Environment set up: VS.Code, PIP, VirtualEnv, Jupyter Notebook, Google Colab

2.1 Using pre-trained networks and third party libraries:

2.1.1 Colorizing images using Colab

2.1.2 Style transfer using Vs.Code

2.1.3 Generating faces using Colab

2.1.4 Generating and summarizing texts using Colab or Vs.Code

3.1 Using Fast.ai and resNet50 with transferlearning

4.1 Our goal is to design a neural network to recognize images

4.2 How can we feed an image to a network?

4.3 What is a network after all? - vectors, matrix, linear algebra

4.4 Backpropagation, activation functions

4.5 We will implement our very first neural nets without any library

4.6 Numpy, Tensors

4.7 Recognizing handwritten digits -MNIST

5.1 Convolutional Neural Network using PyTorch

5.2 Creating image dataset from the web

5.3 Using datasets in PyTorch

5.4 Comparing pre-trained and from scratched networks by implementing both

6.1 One-hot encoding

6.2 Embeddings

6.3 Character level RNN+ LSTM

6.4 Generating text with RNN+LSTM