[Talk] "Become a Data Storyteller with Streamlit" | 🇨🇿 PyData Prague'23 & 🇩🇪 PyMunich'24
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Updated
May 12, 2024 - Python
[Talk] "Become a Data Storyteller with Streamlit" | 🇨🇿 PyData Prague'23 & 🇩🇪 PyMunich'24
A Flask Web App For Diabetes Prediction
A simple machine learning web-based app using flask python
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.
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
SVM model deployed on Azure ACR using Deploifai
Association Mining Deployment as an API Web Application
Sagemaker endpoint deployment with Lambda and API Gateway
This repository hosts a packaged machine learning model designed for predicting passenger survival based on the Titanic dataset.
Source code of team 4 for hacktiv8 Thunder talk.
Machine learning project that predicts whether an email is spam or not.
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.
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.
Get Powerful quotes on your phone or pc!!! NLP WEB APP
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.
Come and check your chances of surviving the titanic in this web app.
Django projects
Image classification model deployment to GCP. Using Streamlit for an interface.
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