Chapter 4. Experiment Management in MLflow
$ cd ~/tmp
$ source stockpred_env/bin/activate
$ cd ~/tmp/Machine-Learning-Engineering-with-MLflow/Chapter04/gradflow/
$ make
$ docker ps
CONTAINER ID IMAGE COMMAND CREATED STATUS PORTS NAMES
3d65aa200d03 gradflow/workbench/jupyter:0.1.0 "tini -g -- start-no…" 19 seconds ago Up 17 seconds 0.0.0.0:8888->8888/tcp, :::8888->8888/tcp gradflow-jupyter-1
0ba4627c9518 gradflow/workbench/mlflow:0.1.0 "/bin/sh -c './wait-…" 19 seconds ago Up 18 seconds 0.0.0.0:5000->5000/tcp, :::5000->5000/tcp gradflow-mlflow-1
fed2e90e166f gradflow/workbench/postgres:0.1.0 "docker-entrypoint.s…" 20 seconds ago Up 18 seconds 0.0.0.0:5432->5432/tcp, :::5432->5432/tcp gradflow-postgres-1
http://localhost:5000
http://localhost:8888
Chapter04/gradflow/notebooks/retrieve_training_data.ipynb
Будем запускать эксперименты
• Logistic Classifier (Chapter04/gradflow/notebooks/mlflow_run_logistic_regression.ipynb) • Xgboost (Chapter04/gradflow/notebooks/mlflow_run_xgboost.ipynb) • Keras (Chapter04/gradflow/notebooks/mlflow_run_keras.ipynb)
Chapter04/gradflow/notebooks/hyperopt_optimization_logistic_regression_mlflow.ipynb