racousin/data_science_practice_2025
Nov 2025 – Nov 2025
1 Month active
Languages Used
Python
Technical Skills
JupyterJupyter NotebookPythondata analysisdata sciencemachine learning
delvTom
PROFILE
Delvtom
Developed a dedicated Exercise 3 Jupyter notebook for the racousin/data_science_practice_2025 repository, focusing on LLM-based math problem solving. The work consolidated setup, data loading, baseline modeling, utilities, prompting strategies, evaluation, and submission generation into a single, reproducible workflow. Using Python and Jupyter Notebook, the developer refined output IDs and tuned model parameters to enhance reliability and performance. The end-to-end submission workflow enabled efficient generation of test set predictions and submission files. This approach accelerated evaluation cycles and improved reproducibility, providing a scalable foundation for math problem solving experiments leveraging data analysis and machine learning techniques with transformers.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
5,730
Activity Months1
Your Network
22 peopleShared Repositories
22
Work History
November 2025
2 Commits • 1 Features
Nov 1, 2025Month 2025-11 — Delivered a focused enhancement to the data science practice repo by introducing a dedicated Exercise 3 Jupyter notebook for LLM-based math problem solving, plus end-to-end submission workflow. The work consolidates setup, data loading, baseline modeling, utilities, prompting strategies, evaluation, and test submission generation, with targeted refinements on output IDs and model parameters for reliability and performance. This accelerates evaluation, reproducibility, and scalability of math problem solving experiments in racousin/data_science_practice_2025.
2 Commits • 1 Features
Nov 1, 2025Month 2025-11 — Delivered a focused enhancement to the data science practice repo by introducing a dedicated Exercise 3 Jupyter notebook for LLM-based math problem solving, plus end-to-end submission workflow. The work consolidates setup, data loading, baseline modeling, utilities, prompting strategies, evaluation, and test submission generation, with targeted refinements on output IDs and model parameters for reliability and performance. This accelerates evaluation, reproducibility, and scalability of math problem solving experiments in racousin/data_science_practice_2025.
November 2025
Activity
Loading activity data...
Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage60.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
JupyterJupyter NotebookPythondata analysisdata sciencemachine learningtransformers
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline