Price_prediction with docker

📖 Table of Contents

1. Introduction 📌
2. Description 📜
3. Installation 🔧
4. Usage and Results 🎮
5. Completion 🏁

📌 Introduction

This project @ BeCode.org as part of the AI Bootcamp in Gent aims at providing prediction in Rest API which runs inside docker and also locally.

📜 Description

• This project is based on collecting data from 10,000 houses.
• Clean and Analyse the data.
• Based on the data predict price value of new house

🔧 Installation

• clone this repository
• use pip install <module name> to install the required models (or)
• use Dockerfile to install and create new image and run a container.

🎮 Usage and Results 📊

Locally

• open the terminal and redirect to where your repository is.
• run the server with uvicorn app:app --reload. whereas app: is the name of .py file and :app is the name of initialisation of FastAPI.
• now open 127.0.0.1:8000 to see welcome page and 127.0.0.1:8000/docs to go to prediction page.
• follow the instructions in schema to enter the details to get the prediction.

Docker deployment - with Docker

I was able to create docker image of size 1.82GB and run docker container to get the same result as my local machine. attaching dockerfile to the repository.

• dowload and install docker desktop in your machine.
• open terminal and redirect to folder where your 'dockerfile' is.
• type docker build -t <image_name> . to create a docker image. (please wait for sometime to create an image)
• type docker run -p 8000:8000 --name <container_name> <image_name> to create new container and run it.
• now open 127.0.0.1:8000 to see welcome page and 127.0.0.1:8000/docs to go to prediction page.
• follow the instructions in schema to enter the details to get the prediction.

🏁 Completion

Name - Mythili Palanisamy
Submission - 28/07/2023 4:00 PM
Team type - solo