end-to-end-recommender-system

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end-to-end-recommender-system

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This is end-to-end-recommender-system repo has full recommender system implementation from collecting data, modeling and deploying machine learning model.

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// repository documentation

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# Description:

This repo contains an end-to-end recommender system model. The code base will contains two main parts:
* notebook: contains the modeling part(feature engineering and building recommender system model).
* service: contains microservice code to serve the model and deploy it to AWS.

Here are some useful commands to run the code locally:

# activate Virtual env:

```
virtualenv venv
python3 -m venv venv
source venv/bin/activate
pip3 install -r requirements.txt 
```
# install and open notebook from the virtual environment:
```
python -m pip install ipykernel
ipython kernel install --user --name=RecommederSystem
jupyter lab &
```
# Build docker image
cd service

docker build -t content-base-recommender .
# run docker container
docker run -d --publish 7777:5000 content-base-recommender

# make sure that the docker run locally (from docker):
http://localhost:7777/recommend/-1479311724257856983

aws configure set region eu-west-1
aws ecr  --region eu-west-1 create-repository --repository-name ecs-recommender-system/home

$(aws ecr get-login  --region eu-west-1 --no-include-email)

docker tag content-base-recommender:latest 477557400504.dkr.ecr.eu-west-1.amazonaws.com/ecs-recommender-system/home:latest

docker push 477557400504.dkr.ecr.eu-west-1.amazonaws.com/ecs-recommender-system/home:latest

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