ipython>=5.5.0
numpy~=1.21
pandas<1.5.0,>=1.3.0
scipy~=1.7.3
joblib~=1.0.1
scikit-learn>=1.0.2
pyod>=0.9.8
imbalanced-learn>=0.8.1
category-encoders>=2.4.0
lightgbm>=3.0.0
numba~=0.55.0
matplotlib>=3.3.0
scikit-plot>=0.3.7
yellowbrick>=1.4
plotly>=5.0.0
kaleido>=0.2.1
statsmodels>=0.12.1
sktime==0.10.1
tbats>=1.1.0
pmdarima>=1.8.0

[analysis]
shap>=0.38.0
interpret>=0.2.7
umap-learn>=0.5.2
ipywidgets>=7.6.5
pandas-profiling>=3.1.0
explainerdashboard>=0.3.8
autoviz>=0.1.36
fairlearn>=0.7.0

[full]
shap>=0.38.0
interpret>=0.2.7
umap-learn>=0.5.2
ipywidgets>=7.6.5
pandas-profiling>=3.1.0
explainerdashboard>=0.3.8
autoviz>=0.1.36
fairlearn>=0.7.0
xgboost>=1.1.0
catboost>=0.23.2
kmodes>=0.11.1
mlxtend>=0.19.0
tune-sklearn>=0.2.1
ray[tune]>=1.0.0
hyperopt>=0.2.7
optuna>=2.2.0
scikit-optimize>=0.9.0
mlflow>=1.24.0
gradio>=2.8.10
fastapi>=0.75.0
uvicorn>=0.17.6
m2cgen>=0.9.0
evidently>=0.1.45.dev0
nltk>=3.7
pyLDAvis>=3.3.1
gensim>=4.1.2
spacy>=3.2.3
wordcloud>=1.8.1
textblob>=0.17.1
psutil>=5.9.0
fugue>=0.6.5

[mlops]
mlflow>=1.24.0
gradio>=2.8.10
fastapi>=0.75.0
uvicorn>=0.17.6
m2cgen>=0.9.0
evidently>=0.1.45.dev0

[models]
xgboost>=1.1.0
catboost>=0.23.2
kmodes>=0.11.1
mlxtend>=0.19.0

[nlp]
nltk>=3.7
pyLDAvis>=3.3.1
gensim>=4.1.2
spacy>=3.2.3
wordcloud>=1.8.1
textblob>=0.17.1

[tuners]
tune-sklearn>=0.2.1
ray[tune]>=1.0.0
hyperopt>=0.2.7
optuna>=2.2.0
scikit-optimize>=0.9.0
