TeKa-Data / klarna_default_ml_pred

This Machine Learning Case Study consists of a supervised learning to predict the probability of default for the datapoints. Once done expose this model with an API Endpoint on AWS cloud provider.

Data analysis

• Document here the project: klarna_default_ml_pred

• Description: This Machine Learning Case Study consists of a supervised learning to predict the probability of default for the datapoints where the default variable is not set. The answer contains the resulting predictions in a csv file with two columns, uuid and pd (probability of default==1). Once done expose this model with an API Endpoint on AWS cloud provider. Then send us the details on how to query the endpoint, attach code used for modelling, a short (max one page) explanation of your model and how you validated it. We mostly use Python for modeling at Klarna. Don’t spend too much time on the prediction results. We evaluate how you structure and reason about the problem rather than the predictive accuracy of your model.

• Data Source: dataset.csv. This is a simple semicolon separated CSV file containing a unique id, the target variable default and a number of features with somewhat different datatypes and meanings. Missing values are denoted as NA in the set. Here is a list of the variables and their types: Column_Name Column_Type uuid text default categorical account_amount_added_12_24m numeric account_days_in_dc_12_24m numeric account_days_in_rem_12_24m numeric account_days_in_term_12_24m numeric account_incoming_debt_vs_paid_0_24m numeric account_status categorical account_worst_status_0_3m categorical account_worst_status_12_24m categorical account_worst_status_3_6m categorical account_worst_status_6_12m categorical age numeric avg_payment_span_0_12m numeric avg_payment_span_0_3m numeric merchant_category categorical merchant_group categorical has_paid boolean max_paid_inv_0_12m numeric max_paid_inv_0_24m numeric name_in_email categorical num_active_div_by_paid_inv_0_12m numeric num_active_inv numeric num_arch_dc_0_12m numeric num_arch_dc_12_24m numeric num_arch_ok_0_12m numeric num_arch_ok_12_24m numeric num_arch_rem_0_12m numeric num_arch_written_off_0_12m numeric num_arch_written_off_12_24m numeric num_unpaid_bills numeric status_last_archived_0_24m categorical status_2nd_last_archived_0_24m categorical status_3rd_last_archived_0_24m categorical status_max_archived_0_6_months categorical status_max_archived_0_12_months categorical status_max_archived_0_24_months categorical recovery_debt numeric sum_capital_paid_account_0_12m numeric sum_capital_paid_account_12_24m numeric sum_paid_inv_0_12m numeric time_hours numeric worst_status_active_inv categorical

• Type of analysis:

Please document the project the better you can.

Startup the project

The initial setup.

Create virtualenv and install the project:

sudo apt-get install virtualenv python-pip python-dev
deactivate; virtualenv ~/venv ; source ~/venv/bin/activate ;\
    pip install pip -U; pip install -r requirements.txt

Unittest test:

make clean install test

Check for klarna_default_ml_pred in github.com/{group}. If your project is not set please add it:

Create a new project on github.com/{group}/klarna_default_ml_pred Then populate it:

##   e.g. if group is "{group}" and project_name is "klarna_default_ml_pred"
git remote add origin [e-mail]:{group}/klarna_default_ml_pred.git
git push -u origin master
git push -u origin --tags

Functionnal test with a script:

cd
mkdir tmp
cd tmp
klarna_default_ml_pred-run

Install

Go to https://github.com/{group}/klarna_default_ml_pred to see the project, manage issues, setup you ssh public key, ...

Create a python3 virtualenv and activate it:

sudo apt-get install virtualenv python-pip python-dev
deactivate; virtualenv -ppython3 ~/venv ; source ~/venv/bin/activate

Clone the project and install it:

git clone [e-mail]:{group}/klarna_default_ml_pred.git
cd klarna_default_ml_pred
pip install -r requirements.txt
make clean install test                # install and test

Functionnal test with a script:

cd
mkdir tmp
cd tmp
klarna_default_ml_pred-run