Developed and Troubleshot Machine Learning Pipeline

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Developed and Troubleshot Machine Learning Pipeline

  • Day: 2024-04-12
  • Time: 19:25 to 20:10
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Machine Learning, Git, Python, Sgdregressor, Gridsearchcv

Description

Session Goal

The goal of this session was to develop a machine learning pipeline using the diamonds dataset, restructure the Git repository, and troubleshoot Git errors.

Key Activities

  • Model Development Plan: Outlined a structured plan for developing a machine learning model, including data preprocessing, model training, evaluation, and addressing production issues.
  • Git Repository Restructuring: Followed a guide to organize and update the Git repository, including adding and removing files and managing commits.
  • Git Error Resolution: Addressed the ‘Couldn’t Find Remote Ref’ error by checking remote branches and setting upstream branches.
  • Local Branch Integration: Integrated the local Git branch with remote repositories using merge and rebase strategies.
  • Git Log Utilization: Used [[git]] log to view and customize commit history.
  • Model Training Code Revision: Revised code for model training using SGDRegressor, including data preprocessing and evaluation.
  • Error Handling in Python: Resolved FileNotFoundError by understanding file paths and setting a default project directory in Python scripts.
  • Grid Search Setup and Analysis: Set up and analyzed GridSearchCV for hyperparameter tuning of SGDRegressor.

Achievements

  • Developed a comprehensive plan for the machine learning model.
  • Successfully restructured the Git repository and resolved Git errors.
  • Revised and improved model training and evaluation code.
  • Set up and analyzed grid search for hyperparameter tuning.

Pending Tasks

  • Further refine the machine learning model based on grid search insights.
  • Continue monitoring and optimizing the Git repository structure.

Evidence

  • source_file=2024-04-12.sessions.jsonl, line_number=1, event_count=0, session_id=788eb60e527504eb6e069365dbf03d955d9d515ee856fd549017fe58c66573fe
  • event_ids: []

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