Second-Hand-Car-Price-Prediction-Using-MLops

WineQuality-Prediction-Using-MLOPS---II

Procedure of Creating a Environment

environment = CarEnv

Activate the env by pasting this on gitbash => source CarEnv/Scripts/activate

init.py -> This file is everywhere in folders as we are using those folders as local packages and in order to import that we have to create init.py

utils are the functions that we use in our code frequently

Workflows

1. Update config.yaml
2. Update schema.yaml
3. Update params.yaml
4. Update the entity
5. Update the configuration manager in src config
6. Update the components
7. Update the pipeline
8. Update the main.py
9. Update the dvc.yaml

About MLflow

MLflow

• Its Production Grade
• Trace all of your expriements
• Logging & tagging your model

MLflow Commands for Dagshub Experiment

MLFLOW_TRACKING_URI=https://dagshub.com/harsh-priyam/Second-Hand-Car-Price-Prediction-Using-MLops.mlflow MLFLOW_TRACKING_USERNAME=harsh-priyam MLFLOW_TRACKING_PASSWORD=d34676be0f7f95c5afd000a5be7be52ce1ba8d12 python script.py

AWS-CICD-Deployment-with-Github-Actions

1. Login to AWS console.

2. Create IAM user for deployment

#with specific access

1. EC2 access : It is virtual machine

2. ECR: Elastic Container registry to save your docker image in aws


#Description: About the deployment

1. Build docker image of the source code

2. Push your docker image to ECR

3. Launch Your EC2 

4. Pull Your image from ECR in EC2

5. Lauch your docker image in EC2

#Policy:

1. AmazonEC2ContainerRegistryFullAccess

2. AmazonEC2FullAccess

3. Create ECR repo to store/save docker image

- Save the URI: 625374339876.dkr.ecr.us-east-1.amazonaws.com/mlproj

4. Create EC2 machine (Ubuntu)

5. Open EC2 and Install docker in EC2 Machine:

#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

6. Configure EC2 as self-hosted runner:

setting>actions>runner>new self hosted runner> choose os> then run command one by one

7. Setup github secrets:

AWS_ACCESS_KEY_ID= AKIAZDGZXEMSC54UW75Q

AWS_SECRET_ACCESS_KEY= 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

AWS_REGION = us-east-1

AWS_ECR_LOGIN_URI = 625374339876.dkr.ecr.us-east-1.amazonaws.com/mlproj

ECR_REPOSITORY_NAME = simple-app