Grandmaster Series - Building a World-Class ML Model for Melanoma Detection

Explore the winning machine learning model for melanoma detection in this 55-minute video from Nvidia's Grandmaster Series. Learn from Kaggle Grandmasters Chris Deotte, Bo Liu, and Gilberto Titericz as they detail their approach to the SIIM-ISIC Melanoma Classification competition. Discover how their model outperforms the average dermatologist in early and accurate melanoma identification. Gain insights into Kaggle competitions, model architecture, data augmentation, training techniques, and competition strategies. Understand the importance of target selection, brute force methods, and model selection in achieving top results. Delve into competition rules, learnings, and modern architectures used in medical imaging challenges. Perfect for data scientists, machine learning enthusiasts, and healthcare professionals interested in cutting-edge AI applications in medical diagnostics.

Introduction
What is Kaggle
Kaggle melanoma classification competition
First place winning solution
Choosing a different target
Model Architecture
Augmentation
Training Details
Brute Force
Model Selection
Competition
Computer Results
Competition Rules
Competition Learnings
Modern Architecture
Google Soccer
pulmonary embolism competition
next episode teaser
Outro