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: 9 months 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 6 years ago)
• Default Branch: master
• Last Pushed: 2022-09-30T19:51:09.000Z (over 3 years ago)
• Last Synced: 2025-02-11T08:48:28.506Z (11 months ago)
• Topics: api, flask, ml, python3, scikit-learn
• Language: Python
• Homepage:
• Size: 9.77 KB
• Stars: 0
• Watchers: 3
• Forks: 0
• Open Issues: 4
• Metadata Files:
  • Readme: README.md

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# 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 Server

Two sample datasets and the request format are included to test out the API.