[Deep Learning 101] Cross-Entropy Loss Function Demystified

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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[@FreelancerRahim-p1j]

Wow very nice

[@bilalviewing]

Wow really great, thanks so much, three probability concepts in one video in followable way!

[@EZlearnAI23]

Glad you like them!

[@LuizHenrique-qr3lt]

I'm marathoning the videos on your channel, do you already have the next theme? I'm looking forward

[@EZlearnAI23]

Thank you for watching! I am trying my best to upload them. I apologize any inconvenience. I will upload asap. Thank you again!

[@LuizHenrique-qr3lt]

GReat explanation!!

[@EZlearnAI23]

Thanks a lot!

[@sharjeel_mazhar]

Your videos are just great ❤🔥 i have only one suggestion for you and that's to make this videos using dark theme. Such a with black background instead of white.

[@EZlearnAI23]

Thank you so much for your comment! I prefer white background. Because you said so, i will consider some dark background ppt some day.

[@vitaliyi2118]

Great explanation, thank you!

[@EZlearnAI23]

Glad it was helpful!

[@wilfredomartel7781]

❤

[@EZlearnAI23]

Thank you!