Jingyong14/HPDP02
May 2025 – Jul 2025
3 Months active
Languages Used
Git AttributesJupyter NotebookMarkdownPythonJSONShell
Technical Skills
Big DataBig Data ProcessingDaskData AnalysisData EngineeringData Optimization
luqmanhakim08
PROFILE
Luqmanhakim08
Muhammad Luqman Hakim developed end-to-end data engineering and analytics solutions in the Jingyong14/HPDP02 repository over three months. He built a real-time news sentiment analysis system that integrated web scraping, Spark ML, Keras, Kafka, and Elasticsearch, enabling live sentiment prediction and dashboard-based monitoring with Kibana. His work included performance benchmarking of Pandas, Polars, and Dask for data loading, as well as establishing reproducible documentation and data packaging infrastructure using Git LFS and Jupyter Notebooks. By focusing on scalable workflows, maintainable code, and production-ready observability, he demonstrated depth in Python, data engineering, and machine learning system integration.
Overall Statistics
Feature vs Bugs
83%Features
Repository Contributions
19Total
Bugs
1
Commits
19
Features
5
Lines of code
144,785
Activity Months3
Work History
July 2025
2 Commits • 2 Features
Jul 1, 2025July 2025 Performance Summary: End-to-end Real-time News Sentiment Analysis System and project scaffolding delivered with emphasis on business value, reliability, and observability. The Real-time system integrates web scraping of articles, training Spark Logistic Regression and Keras LSTM models, and deploying a live prediction service that consumes data from Kafka and stores results in Elasticsearch, with Kibana dashboards to monitor model performance and sentiment trends. Also completed project scaffolding by adding a placeholder Readme.md for 2425/project/p2/Group_5. No major bugs reported this month; all work focused on build-out, integration, and observability. Core technologies demonstrated include Spark ML, Keras, Kafka, Elasticsearch, Kibana, and web scraping.
2 Commits • 2 Features
Jul 1, 2025July 2025 Performance Summary: End-to-end Real-time News Sentiment Analysis System and project scaffolding delivered with emphasis on business value, reliability, and observability. The Real-time system integrates web scraping of articles, training Spark Logistic Regression and Keras LSTM models, and deploying a live prediction service that consumes data from Kafka and stores results in Elasticsearch, with Kibana dashboards to monitor model performance and sentiment trends. Also completed project scaffolding by adding a placeholder Readme.md for 2425/project/p2/Group_5. No major bugs reported this month; all work focused on build-out, integration, and observability. Core technologies demonstrated include Spark ML, Keras, Kafka, Elasticsearch, Kibana, and web scraping.
July 2025
June 2025
3 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for Jingyong14/HPDP02: Focused on delivering performance-oriented data analysis via a benchmarking notebook and improving repository hygiene to support scalable development, onboarding, and audits. The work provides actionable insights for data-stack decisions and enhances maintainability.
June 2025
3 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for Jingyong14/HPDP02: Focused on delivering performance-oriented data analysis via a benchmarking notebook and improving repository hygiene to support scalable development, onboarding, and audits. The work provides actionable insights for data-stack decisions and enhances maintainability.
May 2025
14 Commits • 2 Features
May 1, 2025May 2025 — Jingyong14/HPDP02: Delivered foundational documentation scaffolding and data packaging infrastructure to enable reproducible analytics and scalable data sharing. Key features include readme scaffolding, a concise project overview, and an educational Jupyter notebook documenting NYC taxi data analysis; data assets packaging and large-file handling with Git LFS configuration; and the inclusion of placeholder data and project deliverables (ZIP data, PDFs, PPTX) with repository configuration for large files. No major bugs fixed this month. The work strengthens onboarding, reproducibility, and collaboration, and demonstrates strong capabilities in documentation, data management, and Git-based workflows.
14 Commits • 2 Features
May 1, 2025May 2025 — Jingyong14/HPDP02: Delivered foundational documentation scaffolding and data packaging infrastructure to enable reproducible analytics and scalable data sharing. Key features include readme scaffolding, a concise project overview, and an educational Jupyter notebook documenting NYC taxi data analysis; data assets packaging and large-file handling with Git LFS configuration; and the inclusion of placeholder data and project deliverables (ZIP data, PDFs, PPTX) with repository configuration for large files. No major bugs fixed this month. The work strengthens onboarding, reproducibility, and collaboration, and demonstrates strong capabilities in documentation, data management, and Git-based workflows.
May 2025
Activity
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Quality Metrics
Correctness95.2%
Maintainability94.8%
Architecture95.2%
Performance94.8%
AI Usage20.0%
Skills & Technologies
Programming Languages
Git AttributesJSONJupyter NotebookMarkdownPythonShell
Technical Skills
Big DataBig Data ProcessingDaskData AnalysisData EngineeringData ManipulationData OptimizationData VisualizationDockerDocumentationElasticsearchGit LFSJupyter NotebookJupyter NotebooksKafka
Repositories Contributed To
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