Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
---|---|---|---|---|---|---|---|---|---|---|
Scikit Learn | 57,160 | 18,944 | 11,480 | 2 months ago | 73 | October 23, 2023 | 2,295 | bsd-3-clause | Python | |
scikit-learn: machine learning in Python | ||||||||||
Ydata Profiling | 11,935 | 80 | 116 | 2 days ago | 40 | February 03, 2023 | 221 | mit | Python | |
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames. | ||||||||||
Statsmodels | 9,242 | 3,328 | 2,135 | 2 months ago | 35 | May 05, 2023 | 2,716 | bsd-3-clause | Python | |
Statsmodels: statistical modeling and econometrics in Python | ||||||||||
Gonum | 6,979 | 2,321 | 4 months ago | 110 | August 19, 2023 | 231 | bsd-3-clause | Go | ||
Gonum is a set of numeric libraries for the Go programming language. It contains libraries for matrices, statistics, optimization, and more | ||||||||||
Imbalanced Learn | 6,659 | 140 | 205 | a month ago | 32 | July 08, 2023 | 39 | mit | Python | |
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning | ||||||||||
Growthbook | 5,285 | 11 | 2 months ago | 49 | November 15, 2023 | 302 | other | TypeScript | ||
Open Source Feature Flagging and A/B Testing Platform | ||||||||||
Datascience | 3,955 | 2 months ago | cc0-1.0 | |||||||
Curated list of Python resources for data science. | ||||||||||
Tablesaw | 3,328 | 14 | 24 | 5 months ago | 78 | April 02, 2022 | 130 | apache-2.0 | Java | |
Java dataframe and visualization library | ||||||||||
Xlearn | 3,000 | 1 | 11 | 2 years ago | 10 | December 04, 2018 | 191 | apache-2.0 | C++ | |
High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface. | ||||||||||
Sweetviz | 2,687 | 14 | 4 months ago | 35 | November 29, 2023 | 33 | mit | Python | ||
Visualize and compare datasets, target values and associations, with one line of code. |