Santander Value Prediction Challenge: Open Solution

This is an open solution to the Santander Value Prediction Challenge.

The purpose of the Open Solution

We are building entirely open solution to this competition. Specifically:

1. Check live preview of our work on public projects page: Santander Value Prediction Challenge.
2. Source code and issues are publicly available.

Rules are simple:

1. Clean code and extensible solution leads to the reproducible experimentations and better control over the improvements.
2. Open solution should establish solid benchmark and give good base for your custom ideas and experiments.

Installation

Fast Track

1. Clone repository and install requirements (check requirements.txt)
2. Register to the neptune.ml (if you wish to use it)
3. Run experiment:

neptune run --config neptune_random_search.yaml main.py train_evaluate_predict --pipeline_name SOME_NAME

Step by step

1. Clone this repository

git clone https://github.com/minerva-ml/open-solution-value-prediction.git

2. Install requirements in your Python3 environment

pip3 install requirements.txt

3. Register to the neptune.ml (if you wish to use it)
4. Update data directories in the neptune.yaml configuration file
5. Run experiment:

neptune login
neptune run --config neptune_random_search.yaml main.py train_evaluate_predict --pipeline_name SOME_NAME

6. collect submit from experiment_directory specified in the neptune.yaml

Get involved

You are welcome to contribute your code and ideas to this open solution. To get started:

1. Check competition project on GitHub to see what we are working on right now.
2. Express your interest in paticular task by writing comment in this task, or by creating new one with your fresh idea.
3. We will get back to you quickly in order to start working together.
4. Check CONTRIBUTING for some more information.

User support

There are several ways to seek help:

1. Kaggle discussion is our primary way of communication.
2. Read project's Wiki, where we publish descriptions about the code, pipelines and supporting tools such as neptune.ml.
3. Submit an issue directly in this repo.