Management Dashboard for Torchserve

Pushing Text To Speech models into production using torchserve, kubernetes and react web app 😄

Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]

🔥🔥🔥🔥🧊🔥🔥 A Data Platform for Monitoring and Detecting Anomalies in Real-Time.

In the first course of Machine Learning Engineering for Production Specialization, you will identify the various components and design an ML production system end-to-end: project scoping, data needs, modeling strategies, and deployment constraints and requirements; and learn how to establish a model baseline, address concept drift, and prototype…

An end-to-end Machine Learning project from writing a Jupyter notebook to check the viability of the solution, to breaking down the same into modular code, creating a Flask web app integrated with a HTML template to make a website interface, and deploying on AWS and Azure.

A EKS-based ML deployment solution

Simply Automate Monitoring Infrastructure with Terraform, Ansible, AWS EC2, Nginx, Prometheus, Grafana and Github Actions 😄

An ECS-based ML deployment solution

Deployment of 3D-Detection and Tracking pipeline in simulation based on rosbags and real-time.

This repo shows how to implement a simple image generation app that uses Jax-Implementation of a conditional VAE, Jax, fastapi, docker, streamlit, heroku, ec2, and cloudflare 😃

This project is part of the Udacity Azure ML Nanodegree. In this project, we use Azure to configure a cloud-based machine learning production model, deploy it, and consume it. We also create, publish, and consume a pipeline.

Powerful AutoML toolkit

A regression model to predict calories burnt using values from multiple sensors.

Base classes and utilities that are useful for deploying ML models.

Identifying Patterns and Trends in Campus Placement Data using Machine Learning

A basic example of deploying machine learning applications

Ensemble Learning | Flask

Combine all four layers of analytics (descriptive, diagnostic, predictive, and prescriptive) on crypto data in a dashboard format as a web application.