Esri/arcgis-python-api
Jan 2025 – Jan 2025
1 Month active
Languages Used
Jupyter NotebookPython
Technical Skills
Data ScienceGISLarge Language ModelsMachine LearningNatural Language Processing
Suraj Baloni
PROFILE
Suraj Baloni
During January 2025, Sur11226 developed an end-to-end information extraction notebook for the Esri/arcgis-python-api repository, targeting Cheshire Fire Incident Reports. The project applied data science and natural language processing techniques to automate the extraction of addresses, dates, and incident types from real-world incident texts. Sur11226 integrated the Mistral large language model with the arcgis.learn API, implementing data preparation, model training, evaluation, and inference workflows in Python and Jupyter Notebook. This work demonstrated practical use of LLMs for public safety data analysis, enabling automated entity extraction to support faster incident review and more efficient data capture within GIS workflows.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
1,208
Activity Months1
Your Network
124 people
Work History
January 2025
1 Commits • 1 Features
Jan 1, 2025January 2025: Delivered an end-to-end Information Extraction Notebook for Cheshire Fire Incident Reports leveraging the Mistral LLM and the arcgis.learn API. The notebook covers data preparation, model training, evaluation, and inference, focusing on extracting addresses, dates, and incident types from real-world text. This work demonstrates applying LLMs to practical public-safety data analysis tasks and showcases the value of NLP-driven automation within the Esri/arcgis-python-api ecosystem.
1 Commits • 1 Features
Jan 1, 2025January 2025: Delivered an end-to-end Information Extraction Notebook for Cheshire Fire Incident Reports leveraging the Mistral LLM and the arcgis.learn API. The notebook covers data preparation, model training, evaluation, and inference, focusing on extracting addresses, dates, and incident types from real-world text. This work demonstrates applying LLMs to practical public-safety data analysis tasks and showcases the value of NLP-driven automation within the Esri/arcgis-python-api ecosystem.
January 2025
Activity
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Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture80.0%
Performance60.0%
AI Usage100.0%
Skills & Technologies
Programming Languages
Jupyter NotebookPython
Technical Skills
Data ScienceGISLarge Language ModelsMachine LearningNatural Language Processing
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