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https://github.com/saswatamcode/datascienceapi
This is a RESTful API built using Flask and Scikit-Learn. It provides a host of Classification and Regression algorithms that can be used readily and returns results in the form of predictions, confusion matrices, accuracy scores and more.
https://github.com/saswatamcode/datascienceapi
api flask ml python3 scikit-learn
Last synced: 6 days ago
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This is a RESTful API built using Flask and Scikit-Learn. It provides a host of Classification and Regression algorithms that can be used readily and returns results in the form of predictions, confusion matrices, accuracy scores and more.
- Host: GitHub
- URL: https://github.com/saswatamcode/datascienceapi
- Owner: saswatamcode
- Created: 2019-12-04T05:55:51.000Z (about 5 years ago)
- Default Branch: master
- Last Pushed: 2022-09-30T19:51:09.000Z (over 2 years ago)
- Last Synced: 2025-01-03T11:17:28.185Z (13 days ago)
- Topics: api, flask, ml, python3, scikit-learn
- Language: Python
- Homepage:
- Size: 9.77 KB
- Stars: 0
- Watchers: 3
- Forks: 0
- Open Issues: 4
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Metadata Files:
- Readme: README.md
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README
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[![Open Source Love svg1](https://badges.frapsoft.com/os/v1/open-source.svg?v=103)](https://github.com/ellerbrock/open-source-badges/)# DataScienceAPI
This is a RESTful API built using Flask and Scikit-Learn. It provides a host of Classification and Regression algorithms that can be used readily and returns results in the form of predictions, confusion matrices, accuracy scores and more.## Description
- /rfclassification: Classification using Random Forest algorithm.
- /rfregression: Regression using Random Forest algorithm.
- /svmclassification: Classification using Support Vector Machines algorithm.
- /knnclassification: Classification using K-Nearest Neighbor algorithm.
- /dtclassification: Classification using Decision Trees algorithm.
- /svmregression: Regression using Support Vector Machines algorithm.
- /dtregression: Regression using Decision Trees algorithm.
- /knnregression: Regression using K-Nearest Neighbor algorithm.
- /gnbclassification: Classification using Naive Bayes(Gaussian) algorithm.
- /bnbclassification: Classification using Naive Bayes(Bernoulli) algorithm.
- /logisticregression: Classification using Logistic Regression algorithm.## To Run
- Clone into repo
- Type in `pip install` (preferably inside a virtual environment)
- Then run `python3 main.py`
- Use a REST client to make post requests to the Flask ServerTwo sample datasets and the request format are included to test out the API.