Скачать или смотреть Information Theory Perspective of Cross Entropy Loss | Log Loss | BCE Loss

#bce #crossentropy #KLdivergence #logloss

In this video, we'll be discussing the concept of Cross Entropy Loss, and why it is used as the standard cost function for classification tasks in machine learning and deep learning.

We'll also explore the intuition behind this concept and discuss the mathematics behind it for better understanding.

Also, why we use the concepts of entropy and cross entropy from the information theory, and why cross entropy loss is also referred to as log loss would also be clarified.

We will start with simple case of binary classification and discuss the Binary Cross Entropy Loss, and then extend it for the multi-class case.

Related topics such as KL Divergence are also covered.

If you're interested in ML and DL classification tasks, or want to learn more about Cross Entropy Loss, then be sure to watch this video! By the end, you'll have a better understanding of this important concept, and be able to use it to improve your machine learning and deep learning skills.

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