Add SHAP, LIME, InterpretML under ML and DGL under DL

[YADIDidiah24]

What is this Python project?

This PR adds SHAP, LIME, and InterpretML under Machine Learning and DGL under Deep Learning.

1. SHAP (SHapley Additive exPlanations) provides game-theory-based feature explanations for ML models.
2. LIME (Local Interpretable Model-agnostic Explanations) explains predictions locally by analyzinginputs.
3. InterpretML is a framework for training interpretable models and explaining black-box systems.
   DGL (Deep Graph Library) is a flexible framework designed for deep learning on graphs.

What's the difference between this Python project and similar ones?

Enumerate comparisons.

These libraries are widely used for Explainable AI (XAI) and interpretable machine learning, distinguishing them from general-purpose ML libraries.

DGL vs. Other DL Frameworks: DGL specializes in graph neural networks (GNNs), unlike PyTorch or TensorFlow, which focus on general deep learning.

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