TalkingData AdTracking Fraud Detection Challenge: open solution

This is an open solution to the TalkingData Challenge.

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Check collection of public projects 🎁, where you can find multiple Kaggle competitions with code, experiments and outputs.

Goal

Deliver open source, ready-to-use and extendable solution to this competition. This solution should - by itself - establish solid benchmark, as well as provide good base for your custom ideas and experiments.

Disclaimer

In this open source solution you will find references to the neptune.ml. It is free platform for community Users, which we use daily to keep track of our experiments. Please note that using neptune.ml is not necessary to proceed with this solution. You may run it as plain Python script 😉.

Usage: Fast Track

1. clone this repository: git clone https://github.com/neptune-ml/open-solution-talking-data.git
2. install requirements
3. register to Neptune (if you wish to use it)
4. run experiment:

$ neptune login
$ neptune experiment send --config neptune.yaml --worker gcp-large --environment base-cpu-py3 main.py train_evaluate_predict --pipeline_name solution_1

collect submit from /output/solution-1 directory.

Usage: Detailed

1. clone this repository: git clone https://github.com/neptune-ml/open-solution-talking-data.git
2. install PyTorch and torchvision
3. install requirements: pip3 install -r requirements.txt
4. register to Neptune (if you wish to use it)
5. open Neptune and create new project called: talking-data with project key: TDAT
6. run experiment:

$ neptune login
$ neptune experiment send --config neptune.yaml --worker gcp-large --environment base-cpu-py3 main.py train_evaluate_predict --pipeline_name solution_1

collect submit from /output/solution-1 directory.

User support

There are several ways to seek help:

1. Kaggle discussion is our primary way of communication.
2. You can submit an issue directly in this repo.

Contributing

1. Check CONTRIBUTING for more information.
2. Check issues and project to check if there is something you would like to contribute to.