GitHub topics: model-deploy
rstudio/vetiver-python
Version, share, deploy, and monitor models.
Language: Python - Size: 6.9 MB - Last synced at: 24 days ago - Pushed at: about 1 month ago - Stars: 65 - Forks: 18
khalidw/Operationalizing-Machine-Learning Fork of udacity/nd00333_AZMLND_C2
This is second of the three projects required for fulfillment of the Nanodegree Machine Learning Engineer with Microsoft Azure from Udacity. In this project, we create, publish and consume a Pipeline. We also explore ML model deployment as an HTTP REST API endpoint, swagger API documentation, apache benchmarking of the deployed endpoint and consumption of the endpoint using JSON documents as HTTP POST request.
Language: Jupyter Notebook - Size: 3.36 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0
khalidw/Capstone-Project-Azure-Machine-Learning-Engineer Fork of udacity/nd00333-capstone
This is the Capstone project (last of the three projects) required for fulfillment of the Nanodegree Machine Learning Engineer with Microsoft Azure from Udacity. In this project, we use a dataset external to Azure ML ecosystem. Azure Machine Learning Service and Jupyter Notebook is used to train models using both Hyperdrive and Auto ML and then the best of these models is deployed as an HTTP REST endpoint. The model endpoint is also tested to verify if it is working as intented by sending an HTTP POST request. Azure ML Studio graphical interface is not used in the entire exercise to encourage use of code which is better suited for automation and gives a data scientist more control over their experiment.
Language: Jupyter Notebook - Size: 2.66 MB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 4 - Forks: 2