There are 6 repositories under mlops-project topic.
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
Azure MLOps (v2) solution accelerators. Enterprise ready templates to deploy your machine learning models on the Azure Platform.
End to end machine leanring project: This repository serves as a simplified guide to help you grasp the fundamentals of MLOps.
The project is a concoction of research (audio signal processing, keyword spotting, ASR), development (audio data processing, deep neural network training, evaluation) and deployment (building model artifacts, web app development, docker, cloud PaaS) by integrating CI/CD pipelines with automated tests and releases.
Consignment-Price Prediction project aims to develop a machine learning model that can accurately predict the price of consignment items based on various features and variables
Automated pipeline for energy consumption forecasting across Europe using Azure cloud and Databricks.
An end-to-end MLOps pipeline(CI/CD/CT/CM) project for training, versioning, deploying, and monitoring machine learning models using FastAPI, Kubernetes, MLflow, DVC, Prometheus, and Grafana.
Implementation of classification of grammatically correct sentences and wrong sentences, and integration of MLOps tools.
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 :smiley:
Udacity NanoDegree Course 3 Project "Deploying a Machine Learning Model on Heroku with FastAPI"
Aircraft components are susceptible to degradation, which affects directly their reliability and performance. This machine learning project will be directed to provide a framework for predicting the aircraft’s remaining useful life (RUL) based on the entire life cycle data in order to provide the necessary maintenance behavior.
Handbook for putting applications in the cloud referencing DS and ML paradigms.
This project deploys a diabetes prediction model on AWS using MLOps principles. It features a Flask-based UI for user interaction and utilizes CI/CD pipelines for automated deployment. By leveraging AWS infrastructure, the project ensures scalability, version control, and monitoring of the deployed model.
An application for violent threat detection
Predictive maintenance can help companies minimize downtime, reduce repair costs, and improve operational efficiency. Developing a web application for predictive maintenance can provide users with real-time insights into equipment performance, enabling proactive maintenance, and reducing unplanned downtime.
Official Course Webpage for CS175: Projects in AI
Categorizing IMDB reviews into positive or negative sentiments, emphasizing MLOps practices.
This project understands how the student's performance (test scores) is affected by other variables such as Gender, Ethnicity, Parental level of education, Lunch and Test preparation course.
This is the repository of my study in MLOps Zoomcamp from DataTalksClub.
A repository for Customer Satisfaction ML project 🚀. Using the power of Zenml, this repo ensures seamless integration of Machine Learning Operations.🤖
Repositorio para Bootcamp de Data Science y MLOps 2023 de la Escuela de Datos Vivos
This web application utilizes cutting-edge artificial intelligence to help people understand their risk of developing kidney disease. Developed with user-friendliness in mind, this tool allows individuals to easily enter their information and receive a personalized risk assessment.
Forecasting GDP for IMF member countries
MLOps System for Credit Ranking Project
End to End MLOps Project - Customer Churn Prediction
Semantic Search and offer relevance using Sentence BERT
Binary classification model for predicting diagnosis of asthma
Complete end-to-end MLOps implementation for training, maintaining and monitoring a machine learning model that predicts droughts.
MLOps project Training and Deployment of Churn prediction model
This repository holds all the project files belongs to a Kidney diesease classification application which takes x-rays images and classify the image as dieseased or healthy by using Deep learning CNN classification techniques.
Search in youtube channel
Its main goal wasn't to develop the solution with the best accuracy among others developed by Kaggle's community but rather to understand the applicability of the MLflow framework and how to use it to track different models during the training and evaluation steps, while also learning about the model's versioning and registry.
Project of deploying ML and MLOps