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PyPi packages
lightning 2.0.7
08-24
vaex-jupyter 0.8.2
08-23
vaex 4.17.0
08-23
ludwig 0.8.1.post1
08-16
d3blocks 1.3.1
08-16
barfi 0.7.0
08-09
ydata-profiling 4.4.0
08-08
recommenders 1.1.1
08-05
pre-reco-utils 2021.2.17
08-05
recommender-utils 2021.2.post1623854186
08-05
auto_ml 2.9.10
08-05
pandasai 0.8.2
08-01
vectorbt 0.25.5
07-31
pyoptimus 23.5.0b0
07-31
geomaroc 1.0.3
07-27
geemap 0.25.0
07-22
skypilot 0.3.3
07-14
deeplake 3.6.14
06-28
pandas-summary 0.2.0
06-24
stable-baselines 2.10.2
06-24
optimuspyspark 2.2.32
06-24
creme 0.6.1
06-24
dist-keras 0.2.1
06-18
test-tube 0.7.5
06-18
mage-ai 0.9.10
06-17
pycaret 3.0.4
06-16
autogluon 0.8.2
02-03
plotly-resampler 0.9.1
01-28
fiftyone 0.21.4
01-07
meteostat 1.6.5
01-02
prefect 2.11.2
12-30
akshare 1.10.72
12-30
leafmap 0.23.0
12-30
sweetviz 2.1.4
12-29
gradio 3.39.0
12-29
dtale 3.3.0
12-29
woodwork 0.25.1
12-20
jupyterlab-templates 0.5.0
12-18
pytorch-lightning 2.0.6
12-18
pandas-schema 0.3.6
08-10
modin 0.23.0
08-10
mlxtend 0.22.0
08-10
matrixprofile 1.1.10
08-10
Lifetimes 0.11.3
08-10
lifelines 0.27.7
08-10
kneed 0.8.5
08-10
kfp-server-api 2.0.0
08-10
kfp-pipeline-spec 0.2.2
08-10
kfp 2.1.2
08-10
imbalanced-learn 0.11.0
08-10
h2o 3.42.0.2
08-09
gspread-pandas 3.2.2
08-09
great-expectations 0.17.7
08-09
gluonts 0.13.2
08-09
folium 0.14.0
08-09
feast 0.31.1
08-09
dtreeviz 2.2.2
08-09
dowhy 0.10
08-09
doit 0.36.0
08-09
datacompy 0.10.2
08-09
dagster 1.4.3
08-09
dagit 1.4.3
08-09
combo 0.1.3
08-09
boltons 23.0.0
08-09
autogluon.core 0.8.2
08-09
allennlp 2.10.1
08-09
scikit-learn 1.3.0
08-08
statsmodels 0.14.0
08-08
tensorflow-probability 0.20.1
08-08
awswrangler 3.3.0
08-08
redshift-connector 2.0.913
08-08
ipython 8.14.0
08-08
koalas 1.8.2
08-08
seaborn 0.12.2
08-08
streamlit 1.25.0
08-07
spacy 3.6.0
08-07
pandas 2.0.3
08-07
matplotlib 3.7.2
08-07
keras 2.13.1
08-07
gensim 4.3.1
08-07
posts
Random Data Generation & Data Visualization with Python
07-01