#LIME

Learn to implement LIME for explaining ML model predictions, with hands-on exercises using image classification models and custom Python implementations.

Explore interpretable machine learning with Python, covering LIME and SHAP techniques for explainable AI. Learn why ML explainability matters and how to implement it in your projects.

Explore anti-forensics techniques for Windows, Linux, and Android, covering memory analysis, encryption, and hardware implants. Learn to protect digital evidence and understand forensic challenges.

Explore popular model explanation techniques for machine learning interpretability, including LIME, SHAP, and visual analytics. Gain insights into making complex models more understandable and explainable.

Explore the principles of explainable AI, from feature-based to data-driven models, examining key algorithms like LIME and Shapley while understanding their broader societal impact and applications in search systems.