FPBoost: a gradient boosting model for survival analysis that builds hazard functions as a combination of fully parametric hazards.

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✨.

An interactive Streamlit dashboard for analyzing equipment failure patterns and predicting maintenance needs. Features include data visualization, root cause analysis using Apriori algorithm, and survival modeling with Random Survival Forests to estimate time-to-failure and optimize spare parts management.