diff --git a/README.md b/README.md index ac757c6..5bd322e 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ # 🎓 Student Performance Prediction System -Welcome to the **Student Performance Prediction System** repository! This project uses machine learning to predict student performance based on various features. It leverages Docker for containerization, GitHub Actions for CI/CD, and is deployed on Render for live access. +Welcome to the **Student Performance Prediction System** repository! This project uses machine learning to predict student performance based on various features. It leverages Docker for containerization, GitHub Actions for CI/CD access. ![Capture](https://github.com/user-attachments/assets/43d3185b-f796-4d83-8179-4dad51d14153) @@ -9,9 +9,7 @@ Welcome to the **Student Performance Prediction System** repository! This projec - [Introduction](#introduction) - [Topics Covered](#topics-covered) - [Getting Started](#getting-started) -- [Live Demo](#live-demo) - [Docker and CI/CD](#docker-and-ci-cd) -- [Deploy on Render](#deploy-on-render) - [Best Practices](#best-practices) - [FAQ](#faq) - [Troubleshooting](#troubleshooting) @@ -27,7 +25,7 @@ Welcome to the **Student Performance Prediction System** repository! This projec ## 📖 Introduction -This repository demonstrates a machine learning project focused on predicting student performance based on various features. The project showcases the use of Docker for containerization, CI/CD pipelines with GitHub Actions, and deployment on Render for live demonstrations. +This repository demonstrates a machine learning project focused on predicting student performance based on various features. The project showcases the use of Docker for containerization, CI/CD pipelines with GitHub Actions demonstrations. --- @@ -39,7 +37,6 @@ This repository demonstrates a machine learning project focused on predicting st - **Deployment:** Serving the model using Flask and deploying it as a web service. - **Docker:** Containerizing the application to ensure consistency across different environments. - **CI/CD:** Automating testing and deployment using GitHub Actions. -- **Render:** Deploying the application on Render for online access. --- @@ -86,12 +83,6 @@ To start with this project, follow these instructions: --- -## 🎉 Live Demo - -Explore the live version of the Student Performance Prediction app [here](https://ml-project-student-performance-prediction.onrender.com). - ---- - ## 🐳 Docker and CI/CD ### Docker @@ -127,23 +118,6 @@ Check out the workflow file in `.github/workflows/ci-cd.yml`. --- -## 🌐 Deploy on Render - -Follow these steps to deploy on Render: - -1. **Sign up for Render:** Create an account on [Render](https://render.com). - -2. **Create a new Web Service:** - - Select "New Web Service" from your Render dashboard. - - Connect your GitHub repository. - - Choose your branch (e.g., `main`) and configure build and runtime settings. - -3. **Deploy:** Render will automatically build and deploy your application. - -4. **Access your live app:** Visit the URL provided by Render after successful deployment. - ---- - ## 🌟 Best Practices To maintain and enhance this project, consider the following practices: @@ -220,7 +194,6 @@ Explore the following resources for more information: - **Docker Official Documentation:** [docs.docker.com](https://docs.docker.com/) - **GitHub Actions Documentation:** [docs.github.com](https://docs.github.com/en/actions) -- **Render Documentation:** [render.com/docs](https://render.com/docs) - **Machine Learning Tutorials:** [Kaggle](https://www.kaggle.com/learn/overview) ---