week2 deliverables 100%

[cremerf]

Summary by CodeRabbit

• New Features

  • Introduced multiple notebooks for managing machine learning experiments, model training, logging, and registration using MLflow.
  • Added a new preprocessing module for hotel reservation data with structured logging.
  • Implemented a CancellationModel class for classification tasks related to hotel cancellations.
  • Created a CancellatioModelWrapper class for handling model predictions with MLflow integration.

• Bug Fixes

  • Removed unnecessary entries from version control to improve tracking of relevant files.

• Documentation

  • Added JSON files to document MLflow experiments and model versions for better tracking and management.

• Chores

  • Updated project configuration and dependencies for improved functionality and compatibility.

[coderabbitai]

Caution

Review failed

The pull request is closed.

Walkthrough

The pull request introduces several changes across multiple files, primarily focused on enhancing machine learning workflows using MLflow and Databricks. Key modifications include the addition of new notebooks for managing MLflow experiments, logging, and registering models, as well as updates to configuration files. The .gitignore file has been modified to allow tracking of the prototype directory. Additionally, new JSON files have been created to store experiment and model metadata, and significant updates have been made to existing Python scripts to improve data preprocessing and model management.

Changes

File Path	Change Summary
.gitignore	Removed entry -prototype, allowing the prototype directory to be tracked by Git.
notebooks/02.mlflow_experiment.ipynb	Introduced notebook for managing MLflow experiments, including tracking URI setup, experiment logging, and JSON output.
notebooks/03.log_and_register_model.py	Implemented a workflow for logging and registering a machine learning model using LightGBM and MLflow.
notebooks/04.log_and_register_custom_model.py	Created a script for training and registering a custom model with MLflow.
notebooks/05.log_and_register_fe_model.py	Added a comprehensive workflow for feature engineering and model registration.
notebooks/mlflow_experiment.json	New JSON file defining an MLflow experiment with metadata and attributes.
notebooks/model_version.json	New JSON file containing metadata for a machine learning model.
notebooks/run_info.json	New JSON file with structured information about a specific MLflow run.
project-config.yml	Updated parameters and added new fields in the project configuration.
pyproject.toml	Significant modifications including project name change, exact version dependencies, and new build system section.
src/main.py	Refactored run function to streamline configuration loading and preprocessing logic.
src/mlflow_train.py	Introduced functionality for integrating MLFlow with a model for hotel reservation predictions.
src/packages/classifier.py	Added CancellationModel class for classification tasks with various methods for prediction and evaluation.
src/packages/config.py	Created ProjectConfig class for structured project configuration management.
src/packages/paths.py	Modified AllPaths class to improve configuration handling and environment adaptability.
src/packages/preprocessing.py	Updated Preprocessor class with new methods and improved data handling capabilities.
src/prepare_dataset.py	Introduced a preprocessing module for hotel reservation data using Spark and Pandas.

Possibly related PRs

• Dev #3: The changes in the .gitignore file in the retrieved PR include adding the entry prototype, which is directly related to the modification in the main PR where the line -prototype was removed, allowing the prototype directory to be tracked.

Suggested reviewers

• basakeskili

Poem

In the meadow where data flows,
A rabbit hops where the ML grows.
With models logged and metrics bright,
We dance with joy in the moonlit night.
From prototypes to experiments grand,
Together we build, a data-driven band! 🐇✨

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