YoVDO

SHAP and Shapley Values for Interpretable Machine Learning - Kaggle 30 Days of ML Day 18

Offered By: 1littlecoder via YouTube

Tags

Interpretable Machine Learning Courses Data Science Courses Machine Learning Courses Python Courses Explainable AI Courses Model Interpretability Courses SHAP Courses

Course Description

Overview

Explore SHAP (SHapley Additive exPlanations) and Shapley Values in this 21-minute video tutorial on interpretable machine learning and explainable AI (XAI). Learn why SHAP is necessary, understand its core concepts, and see how it works for local interpretation through practical examples. Dive into Python code for calculating Shapley Values and creating visualizations. Discover alternatives to SHAP and gain insights into making machine learning models more transparent and explainable. Perfect for data scientists and machine learning enthusiasts looking to enhance their understanding of model interpretability techniques.

Syllabus

Kaggle 30 Days of ML (Day 18) - SHAP - Shapley Values - Interpretable Machine Learning - XAI


Taught by

1littlecoder

Related Courses

Machine Learning Interpretable: SHAP, PDP y permutacion
Coursera Project Network via Coursera Machine Learning and AI Foundations: Producing Explainable AI (XAI) and Interpretable Machine Learning Solutions
LinkedIn Learning Guided Project: Predict World Cup Soccer Results with ML
IBM via edX What is Interpretable Machine Learning - ML Explainability - with Python LIME Shap Tutorial
1littlecoder via YouTube How Can I Explain This to You? An Empirical Study of Deep Neural Net Explanation Methods - Spring 2021
University of Central Florida via YouTube