[Talk] "Become a Data Storyteller with Streamlit" | 🇨🇿 PyData Prague'23 & 🇩🇪 PyMunich'24

A simple machine learning web-based app using flask python

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

A Flask Web App For Diabetes Prediction

Association Mining Deployment as an API Web Application

Sagemaker endpoint deployment with Lambda and API Gateway

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

Data analysis and ML Modelling

An end-to-end ML model deployment pipeline on GCP: train in Cloud Shell, containerize with Docker, push to Artifact Registry, deploy on GKE, and build a basic frontend to interact through exposed endpoints. This showcases the benefits of containerized deployments, centralized image management, and automated orchestration using GCP tools.

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

SVM model deployed on Azure ACR using Deploifai

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

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.

Django projects

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.

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

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.

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

A curated collection of AI-powered applications for a versatile and intelligent user experience of Web and Mobile Apps.