Pinned Repositories
cog_Wav2Lip_COLAB_working
This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020.
Credit-Risk-Analysis-for-european-peer-to-peer-lending-firm-Bandora
Machine Learning pipelines are deployed to accomplish the objective of credit risk analysis.
face-anonymization
Hugging-face-pipeline-deployment-via-Flask-and-Fast-APIs
Deployment of NLP Hugging Face pipelines via Flask and Fast APIs
LangChain_Chatbot_Celery_Redis_RabbitMQ_FastAPI
This project is a LangChain-based chatbot integrated with Celery, Redis, RabbitMQ, and FastAPI, designed for efficient asynchronous and synchronous processing. It leverages LangChain's advanced NLP capabilities for enhanced chatbot interactions and uses Redis for managing user session chat history. FastAPI is used for deployment.
locust_load_test_computer_vision_model
Machine-learning-pipeline-deployment-using-Docker-and-FastAPI
This project is focused on the Deployment phase of machine learning. The Docker and FastAPI are used to deploy a dockerized server of trained machine learning pipeline.
RAGMeUp
Generic rag framework to apply the power of LLMs on any given dataset
Ready-to-use-Edge-Detection-using-BDCN
The source code from https://github.com/pkuCactus/BDCN has been modified to make it available as a python function for performing inference using BDCN Model
yolov8_object_detection_counting_tracking_with_supervision_bytetrack
Object Detection, Counting and Tracking Using YoloV8 with Supervision ByteTrack and LineZone Counter.
Arslan-Mehmood1's Repositories
Arslan-Mehmood1/Machine-learning-pipeline-deployment-using-Docker-and-FastAPI
This project is focused on the Deployment phase of machine learning. The Docker and FastAPI are used to deploy a dockerized server of trained machine learning pipeline.
Arslan-Mehmood1/yolov8_object_detection_counting_tracking_with_supervision_bytetrack
Object Detection, Counting and Tracking Using YoloV8 with Supervision ByteTrack and LineZone Counter.
Arslan-Mehmood1/cog_Wav2Lip_COLAB_working
This repository contains the codes of "A Lip Sync Expert Is All You Need for Speech to Lip Generation In the Wild", published at ACM Multimedia 2020.
Arslan-Mehmood1/Credit-Risk-Analysis-for-european-peer-to-peer-lending-firm-Bandora
Machine Learning pipelines are deployed to accomplish the objective of credit risk analysis.
Arslan-Mehmood1/face-anonymization
Arslan-Mehmood1/Hugging-face-pipeline-deployment-via-Flask-and-Fast-APIs
Deployment of NLP Hugging Face pipelines via Flask and Fast APIs
Arslan-Mehmood1/LangChain_Chatbot_Celery_Redis_RabbitMQ_FastAPI
This project is a LangChain-based chatbot integrated with Celery, Redis, RabbitMQ, and FastAPI, designed for efficient asynchronous and synchronous processing. It leverages LangChain's advanced NLP capabilities for enhanced chatbot interactions and uses Redis for managing user session chat history. FastAPI is used for deployment.
Arslan-Mehmood1/locust_load_test_computer_vision_model
Arslan-Mehmood1/RAGMeUp
Generic rag framework to apply the power of LLMs on any given dataset
Arslan-Mehmood1/Ready-to-use-Edge-Detection-using-BDCN
The source code from https://github.com/pkuCactus/BDCN has been modified to make it available as a python function for performing inference using BDCN Model
Arslan-Mehmood1/TEED
TEED: Tiny and Efficient Edge Detector