A collection of notebooks on machine learning engineering and operations.❚
Entry point: 𝗜𝗻𝗲𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗡𝗲𝘁𝘄𝗼𝗿𝗸𝘀 website
The name of this collection comes from the following study:
Brackbill D, Centola D (2020) Impact of network structure on collective
learning: An experimental study in a data science competition. PLoS ONE
15(9): e0237978. https://doi.org/10.1371/journal.pone.0237978
aiofiles 0.8.0
alembic 1.8.0
boto3 1.24.12
cmaes 0.8.2
docker 5.0.3
docker-compose 1.25.5
fastapi 0.75.2
Flask 2.1.2
httpie 3.1.0
isort 5.10.1
joblib 1.1.0
jupyter-book 0.13.0
kaggle 1.5.12
kaleido 0.2.1
keras 2.8.0
loguru 0.5.3
matplotlib 3.5.1
mlflow 1.26.1
mlxtend 0.19.0
numpy 1.22.4
optuna 2.10.0
pandas 1.4.2
pandera 0.10.1
pip 22.0.4
pipenv 2022.6.7
plotly 5.7.0
prefect 2.0b5
pyarrow 7.0.0
pydantic 1.8.2
regression-model-template 0.1.0
scikit-learn 1.0.2
scipy 1.8.1
seaborn 0.11.2
SQLAlchemy 1.4.37
starlette 0.17.1
statsmodels 0.13.2
tensorboard 2.8.0
tensorflow-datasets 4.5.2
tensorflow-macos 2.8.0
tensorflow-metadata 1.7.0
tensorflow-metal 0.4.0
tf-estimator-nightly 2.8.0.dev2021122109
toolz 0.11.2
torch 1.10.2
torchvision 0.11.3
tqdm 4.64.0
uvicorn 0.17.6
xgboost 1.5.1
Model Name: MacBook Air
Model Identifier: MacBookAir10,1
Chip: Apple M1
Total Number of Cores: 8 (4 performance and 4 efficiency)
Memory: 8 GB
System Firmware Version: 7429.61.2
OS Loader Version: 7429.61.2