Raza Rizwan's repositories
Image-Classification-Model-Sagemaker-Connect-To-Lambda-Function
Build image classification model in sagemaker and endpoint connects to Lambda function
End_To_End_Cell_Object_Detection_Using_Yolo_V8_With_Deployment
Successfully concluded YoloV8 Deep Learning project, encompassing MLOps practices, model training facilitated through an intuitive app UI, seamless integration of GitHub Action for automation, and efficient AWS deployment using a robust CI/CD pipeline. Demonstrated expertise in optimizing object detection with cutting-edge techniques.
End_to_End_ML_Project_with_mlflow_and_Deployment
๐ ๐ ๐ฝ๐ฟ๐ผ๐ท๐ฒ๐ฐ๐, encompassing key topics like ๐๐ฎ๐ด๐๐ต๐b and ๐ ๐๐ณ๐น๐ผ๐ for version control, ๐ ๐๐ข๐ฝ๐ practices for efficient deployment, and robust ๐๐/๐๐ ๐ฝ๐ถ๐ฝ๐ฒ๐น๐ถ๐ป๐ฒ setup. Showcased ๐๐ช๐ฆ ๐ฑ๐ฒ๐ฝ๐น๐ผ๐๐บ๐ฒ๐ป๐ with the help of ๐๐ถ๐๐๐๐ฏ ๐๐ฐ๐๐ถ๐ผ๐ป prowess for seamless machine learning application integration.
MLOps-Portfolio
A comprehensive MLOps structure that includes the use of CI/CD pipelines, DVC, MLflow, Git workflow, and Heroku. This structure covers the complete lifecycle of machine learning operations, from continuous integration and deployment pipelines to version control with DVC, experiment tracking with MLflow, collaborative development with Git workflow,
Data-Science-portfolio
In this repository, I have showcased my work in Machine Learning, Deep Learning, and AWS SageMaker. Additionally, I have included my freelancing projects as well.
yolov8-live
A short script showing how to build simple real-time video analytics apps using YOLOv8 and Supervision. Try it out, and most importantly have fun! ๐คช
YOLOv7-DeepSORT-Object-Tracking
YOLOv7 Object Tracking using PyTorch, OpenCV and DeepSORT
typescript-node-projects
Programming Projects to Learn TypeScript and Node.js
machine-learning-notebook
Collection of all of my notes on machine learning, topics span visual recognition, clustering, natural language processing and more.
Learn-Amazon-SageMaker-second-edition
Learn Amazon SageMaker - Second Edition, published by Packt