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sauravmishra1710 / Heart-Failure-Condition-And-Survival-Analysis

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Perform a survival analysis based on the time-to-event (death event) for the subjects. Compare machine learning models to assess the likelihood of a death by heart failure condition. This can be used to help hospitals in assessing the severity of patients with cardiovascular diseases and heart failure condition.

machine-learning exploratory-data-analysis machine-learning-algorithms data-visualization survival-analysis healthcare-datasets cox-regression healthcare-application time-to-event xgboost-algorithm lgbm kaplan-meier-plot heartfailure cardiovascular-diseases kaplanmeierfitter
  • Updated Nov 4, 2023
  • Jupyter Notebook

nisrinaishmh / the-art-of-prompt-engineering

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This project explains "prompt engineering," a key technique for guiding AI models to desired outputs in tools like chatbots and text summarizers. It highlights the importance of clear instructions and techniques like CoT Prompting for effective communication with large language models. The project also introduces the Langchain library✨.

lifelines kaplanmeierfitter prompt-tuning llm prompt-engineering chain-of-thought langchain hugging-face-api scikit-survival n-shot-prompting cot-prompting
  • Updated Feb 29, 2024
  • Jupyter Notebook

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