JohnSnowLabs/spark-nlp-workshop
Apr 2025 – Apr 2025
1 Month active
Languages Used
Python
Technical Skills
Agent DevelopmentEntity RecognitionHealthcare NLPJupyter NotebooksLangChainLarge Language Models
resul
PROFILE
Resul
Resul developed the Healthcare NLP Capabilities Demonstration Notebook for the JohnSnowLabs/spark-nlp-workshop repository, focusing on end-to-end healthcare natural language processing workflows. Using Python and Spark NLP, Resul integrated Hugging Face models and large language models to build pipelines for clinical and medication entity extraction. The notebook featured both general and specialized named entity recognition models, as well as agent-based tools for handling complex queries and identifying critical findings in healthcare data. By establishing a reproducible environment and leveraging Jupyter Notebooks, Resul enabled rapid prototyping and demonstrated the depth of integration between open-source NLP tools and advanced AI models.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
1Total
Bugs
0
Commits
1
Features
1
Lines of code
9,659
Activity Months1
Your Network
18 peopleSame Organization
@johnsnowlabs.com3
Work History
April 2025
1 Commits • 1 Features
Apr 1, 2025April 2025: Delivered the Healthcare NLP Capabilities Demonstration Notebook for the Spark NLP workshop, showcasing end-to-end healthcare NLP pipelines with Spark NLP, Hugging Face model integration, and LLM-driven agents. The solution includes general and specialized NER models for clinical and medication data, and agent-based tools for complex queries and critical finding identification. This work enables rapid prototyping of healthcare NLP workflows, accelerates data-driven insights, and demonstrates strong integration of open-source NLP tools with AI models. Commit: 7a73fad1e0065ce2be9e7941e9c7b9b815d9ce0e.
1 Commits • 1 Features
Apr 1, 2025April 2025: Delivered the Healthcare NLP Capabilities Demonstration Notebook for the Spark NLP workshop, showcasing end-to-end healthcare NLP pipelines with Spark NLP, Hugging Face model integration, and LLM-driven agents. The solution includes general and specialized NER models for clinical and medication data, and agent-based tools for complex queries and critical finding identification. This work enables rapid prototyping of healthcare NLP workflows, accelerates data-driven insights, and demonstrates strong integration of open-source NLP tools with AI models. Commit: 7a73fad1e0065ce2be9e7941e9c7b9b815d9ce0e.
April 2025
Activity
Loading activity data...
Quality Metrics
Correctness80.0%
Maintainability80.0%
Architecture100.0%
Performance80.0%
AI Usage100.0%
Skills & Technologies
Programming Languages
Python
Technical Skills
Agent DevelopmentEntity RecognitionHealthcare NLPJupyter NotebooksLangChainLarge Language ModelsMachine LearningNatural Language ProcessingSpark NLP
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline