ABrain-One/nn-dataset
Jan 2026 – Feb 2026
2 Months active
Languages Used
JSONPython
Technical Skills
PythonPython programmingSQLalgorithm designdata analysisdatabase management
Anujaya Vijayakumar
PROFILE
Anujaya Vijayakumar
Developed a MinHash-based neural network similarity platform for the ABrain-One/nn-dataset repository, focusing on compact model representations and architecture-level similarity indexing to streamline benchmarking and model selection. Leveraged Python and SQL to implement per-model neural network statistics, tokenization, shingling, and MinHash calculations, enabling efficient similarity analysis and diversity-aware querying. Enhanced the platform with a command-line interface and robust SQL-based retrieval, supporting scalable, configurable model discovery workflows. Additionally, improved legacy join reconstruction logic and query parameter validation to ensure data integrity and accurate similarity scoring, establishing a foundation for parameter-driven filtering and more reliable database management in machine learning contexts.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
2
Lines of code
2,127,103
Activity Months2
Your Network
58 peopleShared Repositories
58
pritamMember
CSXizhangMember
ahsan89-ossMember
ABrain-OneMember
ABrain-OneMember
ABrain-OneMember
ABrain-OneMember
ABrain-OneMember
ABrain-OneMember
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary focused on delivering a robust feature in the ABrain-One/nn-dataset repository and addressing stability across legacy join paths. The work emphasizes business value through improved data integrity, accurate similarity scoring, and configurable filtering for query handling.
1 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary focused on delivering a robust feature in the ABrain-One/nn-dataset repository and addressing stability across legacy join paths. The work emphasizes business value through improved data integrity, accurate similarity scoring, and configurable filtering for query handling.
February 2026
January 2026
8 Commits • 1 Features
Jan 1, 2026January 2026: Delivered a MinHash-based Neural Network Similarity Platform for ABrain-One/nn-dataset, enabling compact per-model representations, architecture-level similarity indexing, and SQL-based retrieval to streamline benchmarking and model selection. Implemented per-model NN statistics with code MinHash, introduced architecture-level MinHash index (nn_sim.jsonl.gz), and enhanced similarity tooling with optional diversity queries and a CLI interface. This work improves model discovery, benchmarking efficiency, and supports scalable, diversity-aware model evaluation.
January 2026
8 Commits • 1 Features
Jan 1, 2026January 2026: Delivered a MinHash-based Neural Network Similarity Platform for ABrain-One/nn-dataset, enabling compact per-model representations, architecture-level similarity indexing, and SQL-based retrieval to streamline benchmarking and model selection. Implemented per-model NN statistics with code MinHash, introduced architecture-level MinHash index (nn_sim.jsonl.gz), and enhanced similarity tooling with optional diversity queries and a CLI interface. This work improves model discovery, benchmarking efficiency, and supports scalable, diversity-aware model evaluation.
Activity
Loading activity data...
Quality Metrics
Correctness82.4%
Maintainability82.4%
Architecture86.8%
Performance82.4%
AI Usage42.4%
Skills & Technologies
Programming Languages
JSONPython
Technical Skills
PythonPython programmingSQLalgorithm designdata analysisdatabase managementmachine learningneural networks
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline