Automate entire machine learning pipeline and create end to end solution for given project.

Project : To build a classification methodology to determine whether a person defaults the credit card payment for the next month.

** Entire project explanation provided in creditCardDefaulters.docx file.

Tools & Libraries:

Language : Python3.6

Tools : Docker

Cloud & Database : GCP, MongoDB atlas

Libraries : sklearn, pandas, numpy, flask, GCP-storage, etc..

Command we use to build docker image:

---------------LOCALLY------------------------------

docker image build -t <REPOSITORY>

docker images

docker ps

docker run -p 5000:5000 -d <REPOSITORY>

docker stop <containerID>

docker system prune

----------------In GOOGLE CLOUD PLATFORM-------------------

git clone https://github.com/Tejas2512/CreditCardDefaulters.git

cd CreditCardDefaulters

export PROJECT_ID=creditcarddefaulters

docker build -t gcr.io/${PROJECT_ID}/creditcard:v1 .

docker images

gcloud auth configure-docker gcr.io

docker push gcr.io/${PROJECT_ID}/creditcard:v1

gcloud compute zones list

gcloud config set compute/zone asia-southeast2-a

gcloud container clusters create creditcard --num-nodes=2

kubectl create deployment creditcard --image=gcr.io/${PROJECT_ID}/creditcard:v1

kubectl expose deployment creditcard --type=LoadBalancer --port 80 --target-port 8080

kubectl get service

docker image rm -f <image_id>