Deep Models

Case Study

Revolutionizing Predictive Maintenance - A Hybrid Deep Approach to Remaining Useful Life (RUL) Estimation

A hybrid deep learning approach for predictive maintenance, combining time-frequency feature extraction, advanced AI architectures, and innovative bearing analysis to optimize Remaining Useful Life (RUL) predictions, tackling data sparsity and complex degradation dynamics for industrial reliability.

Case Study

Structured Topic and Sentiment Analysis Pipeline - Group Transitions Dynamics and Emotional Triggers

An advanced NLP pipeline for structured topic and sentiment analysis, leveraging large language models (LLMs), zero-shot labeling, and hierarchical clustering to decode emotional triggers and semantic patterns in online communities for scalable insights.