##create conda env
conda create -p env python==3.8 -y
##activate create conda env
conda activate env/
##install requirements
pip install -r requirements.txt
Always run "python setup.py install" to use modules inside code and converting them to packages
Diamond Price Prediction Introduction About the Data : The dataset The goal is to predict price of given diamond (Regression Analysis).
There are 10 independent variables (including id):
id : unique identifier of each diamond carat : Carat (ct.) refers to the unique unit of weight measurement used exclusively to weigh gemstones and diamonds. cut : Quality of Diamond Cut color : Color of Diamond clarity : Diamond clarity is a measure of the purity and rarity of the stone, graded by the visibility of these characteristics under 10-power magnification. depth : The depth of diamond is its height (in millimeters) measured from the culet (bottom tip) to the table (flat, top surface) table : A diamond's table is the facet which can be seen when the stone is viewed face up. x : Diamond X dimension y : Diamond Y dimension x : Diamond Z dimension Target variable:
price: Price of the given Diamond. Dataset Source Link : https://www.kaggle.com/competitions/playground-series-s3e8/data?select=train.csv
Docker Setup In EC2 commands to be Executed #optinal
sudo apt-get update -y
sudo apt-get upgrade
#required
curl -fsSL https://get.docker.com -o get-docker.sh
sudo sh get-docker.sh
sudo usermod -aG docker ubuntu
newgrp docker
Configure EC2 as self-hosted runner: Setup github secrets: AWS_ACCESS_KEY_ID=
AWS_SECRET_ACCESS_KEY=
AWS_REGION = us-east-1
AWS_ECR_LOGIN_URI = demo>> 566373416292.dkr.ecr.ap-south-1.amazonaws.com
ECR_REPOSITORY_NAME = simple-app