YoVDO

Partial Dependence Plots in Machine Learning Explainability - Day 17 of Kaggle's 30 Days of ML

Offered By: 1littlecoder via YouTube

Tags

Machine Learning Courses Data Visualization Courses Decision Trees Courses Explainable AI Courses

Course Description

Overview

Explore Partial Dependence Plots (PDPs) in this 28-minute video tutorial from the Kaggle 30 Days of ML Challenge. Dive into the world of interpretable machine learning and explainable AI (XAI) by learning what PDPs are, how they differ from feature importance, and when to use them. Discover how to visualize decision tree plots and build PDPs using PDPBox. Gain insights on interpreting PDPs in business language and explore 2D Partial Dependence Plots. Follow along with the provided Kaggle tutorial and exercise to enhance your understanding of this powerful tool for machine learning explainability.

Syllabus

Kaggle 30 Days of ML (Day 17) - Partial Dependence Plot - Interpretable Machine Learning - XAI


Taught by

1littlecoder

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity
Natural Language Processing
Columbia University via Coursera
Probabilistic Graphical Models 1: Representation
Stanford University via Coursera
Computer Vision: The Fundamentals
University of California, Berkeley via Coursera
Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent