Deep Learning for Coders (2020)
Notes from the Deep Learning for Coders (2020) video series by Jeremy Howard and Sylvain Gugger (fast.ai)
Notes from the Deep Learning for Coders (2020) video series by Jeremy Howard and Sylvain Gugger (fast.ai)
Matrix multiplication is a mathematical operation between 2 matrices that returns a matrix.
For each row in the first matrix, take the Dot Productf …
Binary Cross-Entropy (BCE), also known as log loss, is a loss function used in binary or multi-label machine learning training.
It's nearly identical to Negative …
Categorical Cross-Entropy Loss Function, also known as Softmax Loss, is a loss function used in multiclass classification model training. It applies the Softmax Function to …
Cross-entropy measures the average number of bits required to identify an event if you had a coding scheme optimised for one probability distribution
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 …