Layers are the only building blocks in Leaf. As we will see later on, everything is a layer. Even when we construct networks, we are still just -working with layers composed of smalle layers. This makes the API clean and expressive.
+working with layers composed of smaller layers. This makes the API clean and expressive.A layer is like a function: given an input it computes an output. It could be some mathematical expression, like Sigmoid, ReLU, or a non-mathematical instruction, like querying data from a database, logging data, or anything in between. diff --git a/doc/src/layers.md b/doc/src/layers.md index b33c5449..804c080f 100644 --- a/doc/src/layers.md +++ b/doc/src/layers.md @@ -5,7 +5,7 @@ [Layers](./deep-learning-glossary.html#Layer) are the only building blocks in Leaf. As we will see later on, everything is a layer. Even when we construct [networks](./deep-learning-glossary.html#Network), we are still just -working with layers composed of smalle layers. This makes the API clean and expressive. +working with layers composed of smaller layers. This makes the API clean and expressive. A layer is like a function: given an input it computes an output. It could be some mathematical expression, like Sigmoid, ReLU, or a non-mathematical instruction,