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DEPLOYING ML MODELS
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DEPLOYING ML MODELS
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  1. Azure-Databricks-MLflow-Server Public

    Trained 52 ML Regression Models, Registered Model with MLflow, Deployed to Server Endpoint, Tested API Requests

    Jupyter Notebook

  2. yolov8-video-people-counter Public

    Detect people in video then aggregate detections by frame into dataframe and return relevant statistics about numbers of people detected during video.

    Python

  3. AWS-S3-Upload-Load Public

    Upload video file to AWS S3 storage and load video from S3. Your own video file required.

    Python

  4. DSGPT Public

    Ask common python libraries anything! Powered by ChatGPT.

    TypeScript

  5. detectron2-panoptic-segmentation-video Public

    Detectron2 panoptic segmentation demo, video and image.

    Python

  6. XGBoost-Multivariate-Forecasting Public

    Model training, testing, serialization and blind forecasting with XGBoost and lambda regularization.

    Jupyter Notebook 1