Image classification model deployment to GCP. Using Streamlit for an interface.

Source code of team 4 for hacktiv8 Thunder talk.

A Flask Web App For Diabetes Prediction

The model features on the system are all handled by hand gestures. A deep-learning model is used to track the hand and fingers. The tracked fingers then will be made use to generate the click signs and access the other functionalities of the system.

Deploying a clothing classification tensorflow model to an API using tflite, Docker, AWS Lambda and Gateway

In this project, CI/CD pipeline is being created using GitHub Action and Azure DevOps organization

2018年国际AIOps挑战赛KPI时序异常检测比赛基于OpenMLDB部署的工程化部署实践方案

Code and files to go along with CS329s machine learning model deployment tutorial.

Admission Prediction website in US elite colleges. This website uses a Machine Learning model trained using Linear Regression technique. Website takes score as input from users to predict the results based on previously trained Machine Learning model.

Django projects

Machine learning project that predicts whether an email is spam or not.

SVM model deployed on Azure ACR using Deploifai

This repository is an implementation of running python flask app on docker environment. On this project we will detect apples, bananas, and oranges using Yolov5 custom model, and then classify that using Tensorflow custom model. It can be done using image link.

Data analysis and ML Modelling

Come and check your chances of surviving the titanic in this web app.

Get Powerful quotes on your phone or pc!!! NLP WEB APP

Association Mining Deployment as an API Web Application

This repository hosts a packaged machine learning model designed for predicting passenger survival based on the Titanic dataset.

A simple machine learning web-based app using flask python

The Titanic StreamLit Website is an interactive web platform showcasing machine learning models developed for the Kaggle Titanic dataset. The website features a homepage and dedicated pages for Neural Network, Random Forest, and Gradient Boosted Trees models. This project serves as a testament to the deployment of machine learning models.