강의 : https://fullstackdeeplearning.com/
코드 : https://github.com/full-stack-deep-learning/fsdl-text-recognizer-2021-labs

python=3.6
numpy
pillow
matplotlib
h5py
smart_open
toml
nltk
editdistance
pip install boltons wandb pytorch_lightning==1.1.4
pip install torch==1.7.1+cu101 torchvision==0.8.2+cu101 torchaudio==0.7.2 -f https://download.pytorch.org/whl/torch_stable.html

Lab 1: Intro: Formulate problem, structure codebase, train an MLP for MNIST.>실험
Lab 2: CNNs: Introduce EMNIST, generate synthetic handwritten lines, and train CNNs.>실험
Lab 3: RNNs: Using CNN + LSTM with CTC loss for line text recognition.>실험
Lab 4: Transformers: Using Transformers for line text recognition.>실험
Lab 5: Experiment Management: Real handwriting data, Weights & Biases, and hyperparameter sweeps.>실험>wandb
Lab 6: Data Labeling: Label our own handwriting data and properly store it.
Lab 7: Paragraph Recognition: Train and evaluate whole-paragraph recognition.
Lab 8: Continuous Integration: Add continuous linting and testing of our code.
Lab 9: Deployment: Run as a REST API locally, then in Docker, then put in production using AWS Lambda.
Lab 10: Monitoring: Set up monitoring that alerts us when the incoming data distribution changes.