[Deep Learning 101] Cross-Entropy Loss Function Demystified
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- เผยแพร่เมื่อ 26 ม.ค. 2025
- Hello everyone! In this video, we’ll dive into an essential concept in machine learning and deep learning: the 'cross-entropy loss function'. Cross-entropy loss is a measure of how far off a model's predictions are from the actual outcomes. It is widely used because it helps models improve by adjusting their predictions to be more accurate over time. By the end of this video, you'll understand what cross-entropy loss is, how it works, and why it is crucial for training effective models. Stay tuned, and thank you for watching!
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Best video for Cross Entropy and I subscribed and liked.
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Wow really great, thanks so much, three probability concepts in one video in followable way!
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Great explanation, thank you!
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Thank you for watching! I am trying my best to upload them. I apologize any inconvenience. I will upload asap. Thank you again!
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Thank you so much for your comment! I prefer white background. Because you said so, i will consider some dark background ppt some day.
GReat explanation!!
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Gracias!
Glad you like it! Muchas Gracias!
really demystified
❤
Thank you!