HaiAu2501/EL4TF
Aug 2025 – Aug 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data EngineeringData PreprocessingFeature EngineeringFinancial Data AnalysisLSTMMachine Learning
pqnhoang
PROFILE
Pqnhoang
Developed enhancements to the VN30 classification experimentation pipeline in the HaiAu2501/EL4TF repository, focusing on robust financial time series forecasting. Built end-to-end workflows for multi-label and binary classification, integrating data loading, preprocessing, feature engineering, and evaluation with anti-leakage controls and past-data constraints to ensure model integrity. Leveraged Python, Pandas, and PyTorch to support experimentation with LSTM, Random Forest, and XGBoost models. The work consolidated data engineering processes, enabled reliable results export, and accelerated experimentation cycles. These improvements addressed stability issues and established a foundation for production-grade forecasting, emphasizing reproducibility and governance in financial data analysis workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
3Total
Bugs
0
Commits
3
Features
1
Lines of code
1,498
Activity Months1
Your Network
8 peopleShared Repositories
8
Your NameMember
bin1st090104Member
doclautc-1808Member
HaiAu2501Member
LamMember
khangMember
KouhakouuMember
Tamnt240904Member
Work History
August 2025
3 Commits • 1 Features
Aug 1, 2025August 2025 (2025-08) monthly summary for HaiAu2501/EL4TF. Delivered core VN30 classification experimentation pipeline enhancements enabling multi-model experimentation and robust data handling to improve forecast reliability. Implemented end-to-end data loading, evaluation, preprocessing, and feature engineering with anti-leakage controls and past-data constraints to ensure model integrity. Established multi-label and binary classification workflows with evaluation and results export, accelerating experimentation and governance for production forecasting.
3 Commits • 1 Features
Aug 1, 2025August 2025 (2025-08) monthly summary for HaiAu2501/EL4TF. Delivered core VN30 classification experimentation pipeline enhancements enabling multi-model experimentation and robust data handling to improve forecast reliability. Implemented end-to-end data loading, evaluation, preprocessing, and feature engineering with anti-leakage controls and past-data constraints to ensure model integrity. Established multi-label and binary classification workflows with evaluation and results export, accelerating experimentation and governance for production forecasting.
August 2025
Activity
Loading activity data...
Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture83.4%
Performance70.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data EngineeringData PreprocessingFeature EngineeringFinancial Data AnalysisLSTMMachine LearningMulti-label ClassificationNumPyPandasPyTorchPythonRandom ForestScikit-learnTime Series AnalysisXGBoost
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline