kidney-disease-detection-mlops

Kidney Disease Detection using CNN, MLflow, DVC, Docker, and AWS deployment.

Workflows

1.Update config.yaml 2.Update secrets.yaml [Optional] 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 10.app.py

How to run?

STEPS:

Clone the repository

https://github.com/Gavesh99324/kidney-disease-detection-mlops

STEP 01- Create a conda environment after opening the repository

conda create -n cnncls python=3.9 -y

conda activate cnncls

STEP 02- install the requirements

pip install -r requirements.txt

DVC cmd

1. dvc init
2. dvc repro
3. dvc dag

AWS-CICD-Deployment-with-Github-Actions

#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