IBM/watsonx-ai-samples
Nov 2024 – Feb 2025
3 Months active
Languages Used
HTMLPython
Technical Skills
KerasONNXPythonTensorFlowdata sciencemachine learning
Michał Koruszowic
PROFILE
Michał Koruszowic
Michał Koruszowicz contributed to IBM/watsonx-ai-samples by developing and enhancing ONNX model conversion workflows and real-time AI streaming features. He updated documentation and notebooks to support TensorFlow, Keras, LightGBM, CatBoost, and scikit-learn models, ensuring consistency and clarity for data scientists deploying models to ONNX. Michał implemented real-time streaming in the langgraph-react-agent template, enabling dynamic AI responses and improving user experience. His work focused on Python, ONNX, and Jupyter, emphasizing deployment usability and reducing onboarding time. Over three months, he delivered three features with a strong emphasis on documentation quality, workflow standardization, and practical integration for production environments.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
3
Lines of code
45,708
Activity Months3
Work History
February 2025
2 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for IBM/watsonx-ai-samples focusing on feature delivery that enhances ONNX deployment workflows. Delivered end-to-end ONNX model conversion notebooks for LightGBM, CatBoost, and scikit-learn, unified and standardized existing notebooks for consistency, and updated HTML representations and deployment guidance to streamline ONNX-based scikit-learn workflows (installation, training, conversion, deployment) in watsonx.ai Runtime. No major bugs fixed this month; emphasis was on documentation and notebook improvements to boost developer productivity and deployment reliability.
2 Commits • 1 Features
Feb 1, 2025February 2025 monthly summary for IBM/watsonx-ai-samples focusing on feature delivery that enhances ONNX deployment workflows. Delivered end-to-end ONNX model conversion notebooks for LightGBM, CatBoost, and scikit-learn, unified and standardized existing notebooks for consistency, and updated HTML representations and deployment guidance to streamline ONNX-based scikit-learn workflows (installation, training, conversion, deployment) in watsonx.ai Runtime. No major bugs fixed this month; emphasis was on documentation and notebook improvements to boost developer productivity and deployment reliability.
February 2025
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 focused on delivering business value through real-time streaming capabilities in the langgraph-react-agent template within IBM/watsonx-ai-samples. Implemented streaming support to enable dynamic AI responses and improved user experience, with a stable integration ready for broader adoption. No major bugs fixed this month; stabilization and iteration around streaming were prioritized to accelerate time-to-value for downstream applications.
December 2024
1 Commits • 1 Features
Dec 1, 2024December 2024 focused on delivering business value through real-time streaming capabilities in the langgraph-react-agent template within IBM/watsonx-ai-samples. Implemented streaming support to enable dynamic AI responses and improved user experience, with a stable integration ready for broader adoption. No major bugs fixed this month; stabilization and iteration around streaming were prioritized to accelerate time-to-value for downstream applications.
November 2024
1 Commits • 1 Features
Nov 1, 2024Month: 2024-11 — Highlights for IBM/watsonx-ai-samples: Delivered documentation updates for ONNX model conversion (TensorFlow/Keras) to reflect changes, with improved download and conversion steps and added Keras support. Commit ac40cbebf572e551bc66c322ebf5534dc8f26a4f documents alignment with notebook changes and ensures consistency across developer guides.
1 Commits • 1 Features
Nov 1, 2024Month: 2024-11 — Highlights for IBM/watsonx-ai-samples: Delivered documentation updates for ONNX model conversion (TensorFlow/Keras) to reflect changes, with improved download and conversion steps and added Keras support. Commit ac40cbebf572e551bc66c322ebf5534dc8f26a4f documents alignment with notebook changes and ensures consistency across developer guides.
November 2024
Activity
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Quality Metrics
Correctness90.0%
Maintainability80.0%
Architecture80.0%
Performance80.0%
AI Usage80.0%
Skills & Technologies
Programming Languages
HTMLPython
Technical Skills
AI DevelopmentAPI IntegrationData AnalysisData ScienceIBM WatsonInteractive ProgrammingJupyterKerasMachine LearningModel DeploymentONNXPythonTensorFlowdata sciencemachine learning
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