End-to-End-Chest-Cancer-Classification-using-MLflow-DVC

Workflows

Update config.yaml
Update secrets.yaml [Optional]
Update params.yaml
Update the entity
Update the configuration manager in src config
Update the components
Update the pipeline
Update the main.py
Update the dvc.yaml

MLflow

cmd

mlflow ui

dagshub

MLFLOW_TRACKING_URI=https://dagshub.com/ankan89/Pricing_Analytics.mlflow
MLFLOW_TRACKING_USERNAME=ankan89
MLFLOW_TRACKING_PASSWORD=89527c7dee881bd8c8a02e7d2bfc01727ae566a8
python script.py

Run this to export as env variables:

export MLFLOW_TRACKING_URI=https://dagshub.com/ankan89/Pricing_Analytics.mlflow 

export MLFLOW_TRACKING_USERNAME=ankan89

export MLFLOW_TRACKING_PASSWORD=89527c7dee881bd8c8a02e7d2bfc01727ae566a8

DVC cmd

dvc init
dvc repro
dvc dag

About MLflow & DVC

MLflow

Its Production Grade
Trace all of your expriements
Logging & taging your model

DVC

Its very lite weight for POC only
lite weight expriements tracker
It can perform Orchestration (Creating Pipelines)

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: 566373416292.dkr.ecr.us-east-1.amazonaws.com/chicken

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=

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

ankan89 / pricing_analytics Goto Github PK

pricing_analytics's Introduction

End-to-End-Chest-Cancer-Classification-using-MLflow-DVC

Workflows

MLflow

cmd

dagshub

DVC cmd

About MLflow & DVC

AWS-CICD-Deployment-with-Github-Actions

1. Login to AWS console.

2. Create IAM user for deployment

3. Create ECR repo to store/save docker image

4. Create EC2 machine (Ubuntu)

5. Open EC2 and Install docker in EC2 Machine:

6. Configure EC2 as self-hosted runner:

7. Setup github secrets:

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