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https://github.com/tbarlow12/learn-it-your-way

Using Python Flask, I wanted to create a simple web API that allows users to upload a dataset, choose one or more models, store them server side, and then hit an endpoint to get a prediction.
https://github.com/tbarlow12/learn-it-your-way

flask machine-learning python scikit-learn tensorflow

Last synced: 2 months ago
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Using Python Flask, I wanted to create a simple web API that allows users to upload a dataset, choose one or more models, store them server side, and then hit an endpoint to get a prediction.

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## Project Goal
I want to build a simple to use API that allows users to upload a dataset, generate multiple machine learning models and receive an endpoint at which to make predictions in the future
## Project Structure
- app.py - Flask API file
- test.py - Used for testing ML model stuff in console application
- data_tools/
- csv_tools.py - tools for loading and parsing a CSV
- loading.py - tools for saving and loading persistent ML models
- datasets/
- Keeps all datasets uploaded to API. Will be transitioning to some sort of blob storage
- ml_models/
- sklearn.py - Wrapper for any sklearn models we decide to support
- my_models.py - Wrapper for any custom ML models we want to implement
- saved_models/
- Used as storage of persistent ML models