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1
Introduction
2
Welcome
3
Competition
4
Classical Approach
5
Winning Solution
6
Validation Strategy
7
Code Efficiency
8
Modeling
9
Third Place Solution
10
Architecture
11
Finetuning
12
Postprocessing
13
Ensemble
14
Competitions
15
Cutout Augmentation
16
Label Submitting
17
Vaccine Degradation
Description:
Discover advanced techniques for large-scale image classification in this 54-minute video from the Nvidia Grandmaster Series. Learn how Kaggle Grandmasters of NVIDIA (KGMON) built winning models for the Google Landmark Recognition 2020 competition, tackling the challenge of recognizing landmarks across 81,000+ classes. Explore classical approaches, winning solutions, validation strategies, code efficiency, and modeling techniques. Gain insights into third-place solutions, including architecture, fine-tuning, postprocessing, and ensemble methods. Delve into competition-specific strategies like cutout augmentation and label submitting. Led by industry experts, this comprehensive tutorial covers everything from introductory concepts to advanced topics like vaccine degradation, providing valuable knowledge for data scientists and AI enthusiasts interested in computer vision and large-scale image classification challenges.

How to Perform Large-Scale Image Classification

Nvidia
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