Understanding 16 Optimization Regularization Part 1 Modern Computer Vision
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Key Takeaways about 16 Optimization Regularization Part 1 Modern Computer Vision
- We're back with another deep learning explained series videos. In this video, we will learn about
- Deep Learning:
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- In this video, we talk about the L1 and L2
- This video discusses how least-squares regression is fragile to outliers, and how we can add robustness with the L1 norm.
Detailed Analysis of 16 Optimization Regularization Part 1 Modern Computer Vision
For more information about Stanford's online Artificial Intelligence programs visit: https://stanford.io/ai This lecture covers: Ridge Regression is a neat little way to ensure you don't overfit your training data - essentially, you are desensitizing your modelĀ ... Welcome to '
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