A curated collection of AI-powered applications for a versatile and intelligent user experience of Web and Mobile Apps.
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Updated
Oct 13, 2024 - Jupyter Notebook
A curated collection of AI-powered applications for a versatile and intelligent user experience of Web and Mobile Apps.
[Talk] "Become a Data Storyteller with Streamlit" | 🇨🇿 PyData Prague'23 & 🇩🇪 PyMunich'24
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.
Sagemaker endpoint deployment with Lambda and API Gateway
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.
A simple machine learning web-based app using flask python
This repository hosts a packaged machine learning model designed for predicting passenger survival based on the Titanic dataset.
Association Mining Deployment as an API Web Application
Get Powerful quotes on your phone or pc!!! NLP WEB APP
Come and check your chances of surviving the titanic in this web app.
Data analysis and ML Modelling
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.
SVM model deployed on Azure ACR using Deploifai
Machine learning project that predicts whether an email is spam or not.
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.
Code and files to go along with CS329s machine learning model deployment tutorial.
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
In this project, CI/CD pipeline is being created using GitHub Action and Azure DevOps organization
Deploying a clothing classification tensorflow model to an API using tflite, Docker, AWS Lambda and Gateway
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