Categorical Cross-Entropy Loss
Categorical Cross-Entropy Loss Function, also known as Softmax Loss, is a loss function used in multiclass classification model training. It applies the Softmax Activation Function …
Categorical Cross-Entropy Loss Function, also known as Softmax Loss, is a loss function used in multiclass classification model training. It applies the Softmax Activation Function …
Cross-entropy measures the average number of bits required to identify an event if you had a coding scheme optimised for one probability distribution $q …$
Entropy is a measure of uncertainty of a random variable's possible outcomes.
It's highest when there are many equally likely outcomes. As you introduce more …
The Softmax Activation Function converts a vector of numbers into a vector of probabilities that sum to 1. It's applied to a model's outputs (or …
The Sigmoid function squeezes numbers into a probability-like range between 0 and 1.^{1} Used in Binary Classification model architectures to compute loss on discrete …
To prevent cheating, a game needs a rule enforcer.
"if players feel like your game can be cheated, some will try to cheat, but most …
A typical multiplayer game architecture where the server has authority over the game state. The server keeps track of players' positions, the resources they own …
When data is provided to a model that is significantly different from what it was trained on, it's referred to as out-of-domain data.