Sklearnflask
Flask API for training and predicting using scikit learn models
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Machine Learning With Python | 2,980 | a year ago | 8 | bsd-2-clause | Jupyter Notebook | |||||
| Practice and tutorial-style notebooks covering wide variety of machine learning techniques | ||||||||||
| Sklearnflask | 256 | 5 years ago | 5 | mit | Python | |||||
| Flask API for training and predicting using scikit learn models | ||||||||||
| Football_prediction_project | 141 | 4 months ago | mit | Python | ||||||
| This project pulls past game data from api-football, and use these statistics to predict the outcome of future premier league matches through the use of classical machine learning techniques. | ||||||||||
| Python Flask Sklearn Docker Template | 135 | 8 months ago | Python | |||||||
| A simple example of python api for real time machine learning, using scikit-learn, Flask and Docker | ||||||||||
| Stocks | 119 | 2 years ago | 28 | mit | JavaScript | |||||
| machine learning web app game where the user competes against the AI in picking stocks | ||||||||||
| End To End Diabetes Prediction Application Using Machine Learning | 98 | a year ago | 5 | HTML | ||||||
| In this project, the objective is to predict whether the person has Diabetes or not based on various features like Number of Pregnancies, Insulin Level, Age, BMI. | ||||||||||
| A Detector | 56 | 4 years ago | 2 | Python | ||||||
| :star: An anomaly-based intrusion detection system. | ||||||||||
| Predictionapi | 56 | 4 years ago | 1 | mit | Jupyter Notebook | |||||
| Tutorial on deploying machine learning models to production | ||||||||||
| Nba Search | 56 | 2 years ago | 16 | Python | ||||||
| flask application designed to explore NBA data :basketball: | ||||||||||
| Model Deployment Flask | 54 | 5 years ago | 1 | Python | ||||||
| 'Deploying machine learning models with a Flask API' tutorial, written for HyperionDev | ||||||||||
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