PyCaret¶
PyCaret is a “low code” library for machine learning, including AutoML and experiment tracking functionality. It covers a very wide range of ML-related talks and has modules for clustering, regression, classification, anomaly detection, NLP, association rule mining, and time series analysis.
Logo |
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Website |
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Repository |
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Byline |
An open-source, low-code machine learning library in Python. |
License |
MIT |
Project age |
2 years 4 months |
Backers |
Personal Project (Creator and maintainer) |
Lastest News (2021-04-28) |
Release 2.3.1 2.3.1 is a minor release including fixes for CuML wrapper pickleable and exceptions when using Ridge and RF estimator. … more |
Size score (1 to 10, higher is better) |
7.25 |
Trend score (1 to 10, higher is better) |
6.0 |
Education Resources¶
URL |
Resource Type |
Description |
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Documentation |
Official project documentation. |
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https://towardsdatascience.com/predict-lead-score-the-right-way-using-pycaret-332faa780cfc |
Blog |
The blog is written by the creator of the PyCaret project, Moez Ali. This blog is using a lead generation example to walk you through how to use PyCaret. |
Git Commit Statistics¶
Statistics computed using Git data through March 31, 2022.
Statistic |
Lifetime |
Last 12 Months |
---|---|---|
Commits |
52,306 |
8,726 |
Lines committed |
77,344,979 |
7,627,749 |
Unique committers |
84 |
45 |
Core committers |
6 |
14 |

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