EXCEEDS logo
Exceeds
Shivani

PROFILE

Shivani

During January 2025, Shubham Choudhary developed ArcGIS Model Extensibility Notebooks and Deep Learning Package Documentation for the Esri/arcgis-python-api repository. He created two Jupyter notebooks demonstrating model extensibility in ArcGIS, including address standardization using GPT-3.5 and catastrophic event entity recognition with GLiNER. His work included detailed guides for building Esri Deep Learning Packages (.dlpk) for ArcGIS Pro and arcgis.learn, with updates to related documentation for clarity. Shubham’s technical approach leveraged Python, deep learning, and prompt engineering, and he refined implementations based on reviewer feedback, ensuring robust developer-facing features and comprehensive onboarding resources for model extension workflows.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

2Total
Bugs
0
Commits
2
Features
1
Lines of code
2,735
Activity Months1

Work History

January 2025

2 Commits • 1 Features

Jan 1, 2025

Concise monthly summary for 2025-01 focused on delivering developer-facing capabilities and ensuring robust documentation for ArcGIS Python API model extensibility. Key achievements and deliverables included:

Activity

Loading activity data...

Quality Metrics

Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance80.0%
AI Usage50.0%

Skills & Technologies

Programming Languages

JSONJupyter NotebookPython

Technical Skills

ArcGIS API for PythonArcGIS ProDeep LearningDocumentationGLiNERGPT-3.5Model ExtensibilityModel ExtensionNamed Entity Recognition (NER)Natural Language Processing (NLP)Prompt EngineeringZero-shot Learning

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

Esri/arcgis-python-api

Jan 2025 Jan 2025
1 Month active

Languages Used

JSONJupyter NotebookPython

Technical Skills

ArcGIS API for PythonArcGIS ProDeep LearningDocumentationGLiNERGPT-3.5

Generated by Exceeds AIThis report is designed for sharing and indexing