HaiAu2501/EL4TF
Aug 2025 – Aug 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data PreprocessingDeep LearningMachine LearningPandasPyTorchPython
doclautc-1808
PROFILE
Doclautc-1808
Developed scalable stock data classification experiments for the HaiAu2501/EL4TF repository, focusing on VN30 equities. Built both multi-class and binary classification workflows using multilayer perceptron models, leveraging Python, PyTorch, and Scikit-learn within Jupyter Notebook environments. Designed per-stock training pipelines with individual checkpoints to ensure reproducibility and facilitate deployment-ready experimentation. Integrated data preprocessing steps, including StandardScaler, and implemented aggregated evaluation using balanced accuracy across multiple stock files. The notebook-driven approach enabled rapid iteration and clear experiment tracking, supporting business needs for per-stock model evaluation and scalable workflows in time series analysis and machine learning applications.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
2Total
Bugs
0
Commits
2
Features
1
Lines of code
822
Activity Months1
Your Network
8 peopleShared Repositories
8
Your NameMember
bin1st090104Member
pqnhoangMember
HaiAu2501Member
LamMember
khangMember
KouhakouuMember
Tamnt240904Member
Work History
August 2025
2 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for HaiAu2501/EL4TF: Delivered scalable VN30 stock data classification experiments with per-stock training and notebook-based workflows. Implemented an MLP-based multi-class classification model and established a binary-class workflow with data loading, StandardScaler preprocessing, and aggregated evaluation using balanced accuracy across available stock files. Created per-stock checkpoints and experiment scaffolding to support reproducible, deployment-ready experimentation. This work demonstrates strong technical capabilities in Python-based ML pipelines, data preprocessing, model evaluation, and notebook-driven experimentation, while delivering business value through per-stock signals and scalable workflows.
2 Commits • 1 Features
Aug 1, 2025August 2025 monthly summary for HaiAu2501/EL4TF: Delivered scalable VN30 stock data classification experiments with per-stock training and notebook-based workflows. Implemented an MLP-based multi-class classification model and established a binary-class workflow with data loading, StandardScaler preprocessing, and aggregated evaluation using balanced accuracy across available stock files. Created per-stock checkpoints and experiment scaffolding to support reproducible, deployment-ready experimentation. This work demonstrates strong technical capabilities in Python-based ML pipelines, data preprocessing, model evaluation, and notebook-driven experimentation, while delivering business value through per-stock signals and scalable workflows.
August 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage20.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data PreprocessingDeep LearningMachine LearningPandasPyTorchPythonScikit-learnTime Series Analysis
Repositories Contributed To
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