ML Interpretability and Explainability

Free

Intermediate

2h

11 lessons

Learn to interpret machine learning models through hands-on implementation of SHAP, LIME, GradCAM, and other essential techniques.

Machine Learning

Interpretability

Explainability

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Lessons

1

Introduction to ML Interpretability and Explainability

2

Intrinsic Model Interpretability & Surrogate Methods

3

Feature Importance & Global Interpretation Techniques

4

Model-Agnostic Methods & SHAP Values

5

Local Explainability with LIME & SHAP

Back to Path

ML Interpretability and Explainability

Free

Intermediate

2h

11 lessons

Learn to interpret machine learning models through hands-on implementation of SHAP, LIME, GradCAM, and other essential techniques.

Machine Learning

Interpretability

Explainability

Sign In Required

Create an account or sign in to access the lesson content

Sign Up Sign In

Lessons

1

Introduction to ML Interpretability and Explainability

2

Intrinsic Model Interpretability & Surrogate Methods

3

Feature Importance & Global Interpretation Techniques

4

Model-Agnostic Methods & SHAP Values

5

Local Explainability with LIME & SHAP

6

Hands-On #1

60 min

7

Deep Learning Interpretability Methods

8

Visual Interpretation Techniques for Neural Networks

9

Quiz #1

10

Hands-On #2

60 min

11

ML Interpretability and Explainability

Lessons

Introduction to ML Interpretability and Explainability

Intrinsic Model Interpretability & Surrogate Methods

Feature Importance & Global Interpretation Techniques

Model-Agnostic Methods & SHAP Values

Local Explainability with LIME & SHAP

ML Interpretability and Explainability

Lessons

Introduction to ML Interpretability and Explainability

Intrinsic Model Interpretability & Surrogate Methods

Feature Importance & Global Interpretation Techniques

Model-Agnostic Methods & SHAP Values

Local Explainability with LIME & SHAP

Hands-On #1

Deep Learning Interpretability Methods

Visual Interpretation Techniques for Neural Networks

Quiz #1

Hands-On #2

Quiz #2