Webscikit
Webscikit is a set of tools to run a webserver as a JSON Webservice for scikit-learn predictions. It comes with two examples: boston and boston2
| Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
|---|---|---|---|---|---|---|---|---|---|---|
| Cape Webservices | 132 | 6 years ago | 4 | apache-2.0 | Python | |||||
| Entrypoint for all backend cape webservices | ||||||||||
| Support Tickets Classification | 128 | 3 years ago | 4 | mit | Python | |||||
| This case study shows how to create a model for text analysis and classification and deploy it as a web service in Azure cloud in order to automatically classify support tickets. This project is a proof of concept made by Microsoft (Commercial Software Engineering team) in collaboration with Endava http://endava.com/en | ||||||||||
| Rsdmx | 95 | 12 | 11 | 4 months ago | 22 | September 21, 2018 | 15 | R | ||
| Tools for reading SDMX data and metadata in R | ||||||||||
| Recommendationengine | 70 | 7 years ago | C# | |||||||
| Recommendation Engine using Azure ML Studio to recommend related movies. | ||||||||||
| Timecop | 54 | 4 years ago | 7 | May 11, 2020 | 9 | apache-2.0 | Python | |||
| Time series based anomaly detector | ||||||||||
| Swppfall2019 | 34 | 3 years ago | 245 | HTML | ||||||
| Deploy Ml Model | 33 | 5 years ago | 1 | mit | Jupyter Notebook | |||||
| Deploying a simple machine learning model to an AWS ec2 instance using flask and docker. | ||||||||||
| Cntk Python Web Service On Azure | 25 | 6 years ago | 2 | mit | Python | |||||
| This sample project shows off how to prepare and deploy to Azure Web Apps a simple Python web service with an image classifying model produced in CNTK (Cognitive Toolkit) using FasterRCNN | ||||||||||
| Ml Prediction Web Service | 15 | 7 months ago | apache-2.0 | Python | ||||||
| A simple python web service to host an ML model for prediction. | ||||||||||
| Ml Service Production | 10 | 3 years ago | n,ull | mit | Python | |||||
| This project is made to help you scale from a basic Machine Learning project for research purposes to a production grade Machine Learning web service | ||||||||||
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