Alexis Bruneteau ff71d052e6
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Track individual model files instead of single multitask model
The training script creates separate model files for each task
(match_winner, map_winner, score_team1, score_team2, round_diff, total_maps)
so DVC needs to track each file individually.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-10-01 20:55:28 +02:00
2025-09-30 17:03:15 +02:00
2025-09-30 17:03:15 +02:00
2025-10-01 17:35:13 +02:00
2025-10-01 15:04:13 +02:00
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2025-09-30 16:38:14 +02:00
2025-09-30 15:48:38 +02:00
2025-10-01 15:04:13 +02:00

MLOps Project

This is an MLOps project for CSGO data analysis and model training.

Features

  • Data pipeline with Apache Airflow
  • Model training with PyTorch and scikit-learn
  • MLflow for experiment tracking
  • DVC for data versioning
  • Monitoring with Prometheus
  • FastAPI for API serving

Setup

  1. Install dependencies:

    poetry install
    
  2. Run the data pipeline:

    airflow dags unpause csgo_data_pipeline
    

Project Structure

  • dags/: Airflow DAGs
  • src/: Source code
  • models/: Trained models
  • data/: Data files
  • notebooks/: Jupyter notebooks
  • tests/: Test files
  • config/: Configuration files
  • docker/: Docker files
  • kubernetes/: Kubernetes manifests
Description
No description provided
Readme 350 KiB
Languages
Python 73.3%
Typst 25.9%
Dockerfile 0.8%