yashk1 / ML-end-to-end

Full deployment of machine learning project

ML-end-to-end

Full deployment of machine learning project

Requirements

1. Github
2. Heroku
3. VS code
4. Git CLI

Creating Conda env

conda create -p venv 

Activate conda

conda activate penv

Create requirements.txt

#install requirements
pip install -r requirement.txt

Git Commands

To check all version maintained by git

git log

To create version/ commit all files

git commit -m "message"

To send version/changes to git

git push origin main

To check remote url

git remote -v

Heroku

To setup CI/CD pipeline in heroku we need 3 information

1. HEROKU_EMAIL = [e-mail]
2. HERKOU_API_KEY = <>
3. HEROKU_APP_NAME = ml-regression-basic

Docker

Build Docker image

docker build -t <image-name>:<tagname> .

Note: Image name for docker must be lowercase

To list docker images

docker images

Run docker image

docker run -p 4000:4000 -e PORT=4000 d702d2637a7e

To check running containers

docker ps

To stop docker coantainer

docker stop <container-id>

Remove a container