Price predictions for 3DHubs
Project description
Price Prediction
Replicate / Reproduce Whole Process
Training Process
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Pre-requirements:
- Install conda: link
- Install MLFlow:
pip install mlflow
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Run Mlflow UI server to track the training experiments:
cd train/ mlflow server --backend-store-uri ./mlruns/
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Train:
# working dir: "ml-engineer-assignment-bendangnuksung/train/" # modify "train/MLproject" file, update parameters such as: # 'datapath' -> path to your data CSV file (important) # 'kfolds' -> N kfolds you want # 'lr' -> Set your own learning rate # Run training mlflow run --experiment-name hubs_price_prediction .
Deployment Process
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Pre-requirements:
- Install Docker. Link
- Install Docker Compose:
pip install docker-compose
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Build and Start Docker:
# working dir: "ml-engineer-assignment-bendangnuksung/" # Modify "docker-compose.yml" if: # 1. Wants to change PORT # 2. Change the volumes if model stored in different directory. (Default is: "./train/models" because models are stored there after training) sudo docker-compose up
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