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performance-evaluation-metrics

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RatnaKaturi / Analyzing-Attention-Head-Specialization-in-Transformer-Language-Models

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Performed head-level interpretability analysis on Transformer models using masking experiments. Evaluated attention head contribution through accuracy and logit-based metrics (91% baseline accuracy).

natural-language-processing deep-learning multi-head-attention model-interpretability performance-evaluation-metrics tranformer-architecture self-attention-mechansim attention-head-specialization masking-experiments model-robustness-analysis
  • Updated Feb 21, 2026
  • Jupyter Notebook

Lucky-akash321 / End-to-End-Machine-Learning-Projects

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End-to-end machine learning projects involve the complete process of developing a machine learning model, starting from data collection and preprocessing to training, evaluation, and deployment. These projects encompass data exploration, feature engineering, model selection, performance evaluation, and integration with production systems

machine-learning-model-deployment data-collection-and-preprocessing model-training-and-tuning feature-engineering-techniques performance-evaluation-metrics real-time-prediction-systems automation-in-ml-pipelines model-monitoring-and-maintenance
  • Updated Feb 25, 2025
  • Jupyter Notebook

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