Understanding Binary Cross-Entropy / Log Loss in 5 minutes: a visual explanation

If you are training a binary classifier, chances are you are using binary cross-entropy / log loss as your loss function.
Have you ever thought about what exactly does it mean to use this loss function? This video explains the concepts behind binary cross-entropy / log loss in a visually clear and concise manner.
The content of this video is also available in the corresponding blog post: towardsdatasci...

[@CowboyRocksteady]

thank you so much! the blog post that bought me here was phenomenal!

[@radioactivebuzz]

Great video, but in case anyone else is confused: 3:31 should already have the minus signs outside log (i.e. -log) to match with the on-screen diagram.

[@altay8832]

yess

[@DamienTANNEAU]

I agree

[@nicolenlama]

Simply amazing. Thank you for this much needed refresher

[@alikhanaitbayev4191]

Thank you. Please release more videos in such format.

[@matruiz1918]

best explanation by far. great effort making the animations

[@IgorKuts]

Thank you, Sir, for this brilliant video and the corresponding blog post.

[@JohnSegrave]

This is super content - really nicely done! You should do more of these - this one was great, I'd love to see more (I subscribed). The equation colouring and mapping to the visual is *so incredibly useful* (looks like 3b1b's Manim?).

[@dimastorres8530]

neat and brief. Than you

[@emransaleh9535]

Well explained! Good Job!

[@bugaboo6819]

Thank you!

[@user-bw3vh8hq2e]

Smooooch )

[@funkie1221]

Great explanation. The animations are a bit distracting and also you could keep the bars up when you show the formula, would be helpful! Otherwise brilliant!!

[@fernandoerazo8135]

chat gpt brought me here . Lets goo