This solution accelerator purpose is also to ease the integration of Data science modules into your knowledge mining solution.
The Data Science Toolkit team has built accelerators for your data science workload.
| Solution | Description |
|---|---|
| Verseagility | Verseagility is a Python-based toolkit to ramp up your custom natural language processing (NLP) task, allowing you to bring your own data, use your preferred frameworks and bring models into production. It is a central component of the Microsoft Data Science Toolkit. |
| MLOps Base | This repository contains the basic repository structure for machine learning projects based on Azure technologies (Azure ML and Azure DevOps). The folder names and files are chosen based on personal experience. You can find the principles and ideas behind the structure, which we recommend to follow when customizing your own project and MLOps process. Also, we expect users to be familiar with azure machine learning concepts and how to use the technology. |
| MLOps for DataBricks | This repository contains the Databricks development framework for delivering any Data Engineering projects, and machine learning projects based on the Azure Technologies. |
| Classification Solution Accelerator | This repository contains the basic repository structure for delivering classification solutions for machine learning (ML) projects based on Azure technologies (Azure ML and Azure DevOps). |
| Object Detection Solution Accelerator | This repository contains all the code for training TensorFlow object detection models within Azure Machine Learning (AML) with setups for training on Azure compute, experiment monitoring and endpoint deployment as a webservice. It is built on the MLOps Accelerator and provides end to end training and deployment pipelines allowing quick and easy setup of CI/CD pipelines for your projects. |