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.
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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
- Neural Networks and Deep Learning
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)
- https://jlibovicky.github.io/ (mostly about Machine Translation)
- https://yashuseth.blog/ (general ML topics)
- 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)
- 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
- 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