Entry point: OK Transformer website
A collection of self-contained notebooks on topics in machine learning engineering and operations. The notebooks run end-to-end with generally reproducible results across runs.
Making a local build:
git clone git@github.com:particle1331/ok-transformer.git
cd ok-transformer
pip install -r build-requirements.txt
make docs
Should be okay to within micro or minor releases:
docker 5.0.3
docker-compose 1.25.5
fastapi 0.75.2
keras 2.8.0
matplotlib 3.5.1
mlflow 1.26.1
numpy 1.22.4
optuna 2.10.0
pandas 1.4.2
pipenv 2022.6.7
prefect 2.0b5
scikit-learn 1.0.2
seaborn 0.11.2
tensorflow-datasets 4.5.2
tensorflow-macos 2.8.0
tensorflow-metal 0.4.0
torch 1.13.0
torchvision 0.14.0
uvicorn 0.17.6
xgboost 1.6.0.dev0
P100 Kaggle kernel or equivalent with the ff. specs should be sufficient:
GPU 0: Tesla P100-PCIE-16GB (UUID: GPU-543c532b-c511-c675-a565-bf01208405e0)
Model name: Intel(R) Xeon(R) CPU @ 2.00GHz
Socket(s): 1
Core(s) per socket: 1
Thread(s) per core: 2
L3 cache: 38.5 MiB
CPU MHz: 2000.188
MemAvailable: 15212104 kB
Avail
67G