Debugging and Resolving ML and Web Errors
- Day: 2024-04-14
- Time: 18:45 to 19:45
- Project: Dev
- Workspace: WP 2: Operational
- Status: Completed
- Priority: MEDIUM
- Assignee: Matías Nehuen Iglesias
- Tags: Debugging, Machine Learning, Web Development, Javascript, Error Handling
Description
Session Goal
The session aimed to troubleshoot and resolve various errors encountered in machine learning preprocessing and web development.
Key Activities
- Resolved OneHotEncoder Category Mismatch Error: Addressed category mismatches during transformation in machine learning using OneHotEncoder.
- Inspected Preprocessor in Jupyter Notebook: Loaded and inspected a preprocessor saved as a .joblib file using joblib in Jupyter Notebook.
- Expanded Debugging for Preprocessing Issues: Enhanced logging during preprocessing in a machine learning pipeline to diagnose failures.
- Resolved Feature Mismatch in ML Models: Tackled feature mismatch issues between training and prediction phases using OneHotEncoder.
- Fixed Model Name Handling in JS and Flask Integration: Updated Flask endpoint and JavaScript to handle new model names.
- Resolved ‘Plotly is not defined’ Error: Provided steps to include Plotly library correctly in HTML to avoid errors.
- Handled Favicon 404 Error: Offered solutions for favicon-related 404 errors in web development.
- Resolved Plotly DOM Element Error: Addressed DOM element errors in JavaScript related to Plotly.
Achievements
- Successfully resolved multiple machine learning preprocessing and web development errors, improving the robustness of the systems.
Pending Tasks
- Further testing is required to ensure all changes integrate smoothly across the entire system.
- Monitor for any additional issues that may arise from these fixes.
Evidence
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- event_ids: []