README.md

I created this repo to log my progress of studying deep learning and also to share blog/article links that may be useful to other ppl.

1. Courses I am taking

• Andrew Ng's Machine Learning 02/Aug/2020 - 22/Aug/2020

• Andrew Ng's Deep Learning 29/Aug/2020 -

  • Neural Networks and Deep Learning 29/Aug/2020 - 08/Sep/2020
  • Improving Deep Neural Networks 08/Sep/2020 -
  • Structuring Machine Learning Projects
  • Convolutional Neural Networks
  • Sequence Models

2. Books to read

• Linear Algebra and Its Applications
• Deep Learning by Ian Goodfellow

3. References

• How to learn deep learning [video]

4. Links to checkout later

Courses

• CS231n: Convolutional Neural Networks for Visual Recognition
• CS224n: Natural Language Processing with Deep Learning
• CS109: Probability for Computer Scientists
• Coursera NLP Specialization

Links

• http://neuralnetworksanddeeplearning.com/
• https://www.deeplearningbook.org/
• https://spinningup.openai.com/en/latest/index.html
• https://ml-cheatsheet.readthedocs.io/ (cheat sheet)

5. Blogs I following

• https://jlibovicky.github.io/ (mostly about Machine Translation)
• https://yashuseth.blog/ (general ML topics)

6. Questions I have searched

General

• How to create a good validation set
• How to Use Dropout with LSTM Networks for Time Series Forecasting
• How to define your machine learning problem
• Continuous video classification with TensorFlow, Inception and Recurrent Nets
• Gentle Introduction to Dropout for Regularizing Deep Neural Networks
• How to Avoid Overfitting in Deep Learning Neural Networks
• optim.Adam vs optim.SGD in Pytorch
• Learning Rate Schedules and Adaptive Learning Rate Methods for Deep Learning
• Transfer Learning - Machine Learning's Next Frontier
• Transfer Learning Tips (Fine-tuning vs Fixed feature extractor)

Neural Nets

• About Resnet34
• ML is fun! Deep Learning and CNN
• A Comprehensive Guide to Convolutional Neural Networks — the ELI5 way
• CNN vs RNN: Which Neural Network Is Right for You?
• Unet explanation in details
• CNN LSTM Networks
• When to Use MLP, CNN, and RNN Neural Networks
• Gentle Introduction to Pooling Layers for CNN
• Introduction to ANN
• Batch Normalization and Dropout in Neural Networks with Pytorch
• A Simple Way to Prevent Neural Networks from Overfitting - Paper

NLP

• An Intuitive Understanding of Word Embeddings: From Count Vectors to Word2Vec
• How to do Semantic Segmentation using Deep learning
• A Comprehensive Guide to Build your own Language Model in Python!
• The Illustrated Transformer (NLP)
• Fastai with 🤗Transformers (BERT, RoBERTa, XLNet, XLM, DistilBERT)
• Stemming and Lemmatization in Python
• How I used deep learning to talk like me
• NLP Explanation
• Build your own speech-to-text with Python
• Neural Machine Translation
• Part1: BERT for Advance NLP with Transformers in Pytorch
• Introduction to PyTorch-Transformers: An Incredible Library for State-of-the-Art NLP
• Neural Machine Translation

Unsupervised Learning

• How can Unsupervised Neural Machine Translation Work?
• Unsupervised Machine Translation