Intro_Deep_Learning

I'm taking "Introduction to Deep Learning with PyTorch" lecture from Udacity.

This repository includes my notes & codes from this lecture. I also take screenshots to remember the concepts easily. There are also some useful links and my own notes.

I would like to thank Udacity to give us opportunity to reach these course free:)

• Introduction to Deep Learning with PyTorch
• The original codes

The outline of the repository

1. common This folder includes common scripts which are used for the entire project.

2. Intro_NN Introduction to Neural Networks. Before using the torch modules it is useful to understand the maths behind gradients, perceptron, regularization. I also add some of my handwritten notes not to forget the derivatives :)

3. Intro_Pytorch_Lecture Learn how to develeop a neural network with PyTorch. Mnist Data Set, Mnist Fashion Data Set and Cat & Dog images are used for classification

4. MLP This is a recap for MLP. You can find complete classification code for Mnist dataset and analysis of these codes

5. CNN

   • Filtering, visualization, cifar-10-images
   • You may find the assignments for knn, svm, softmax, gradient from the lecture cs231n from Standford University

6. RNN Includes, text prediction, time series analysis

7. Sentiment Analysis Sentiment analysis with RNN

8. text_mining Small example for text mining

9. Style Transfer Style transfer with VGG-19