minor edits

_posts/2024-05-21-keras3/introducing-keras3.Rmd

@@ -27,7 +27,7 @@ beloved features of the original while refining and simplifying the API
 based on valuable insights gathered over the past few years.
 
 Keras provides a complete toolkit for building deep learning models in
-R---it's never been easier to build, train, evaluate and deploy deep
+R---it's never been easier to build, train, evaluate, and deploy deep
 learning models.
 
 ## Installation
@@ -118,19 +118,19 @@ trackbacks while debugging.
 Keras 3 also lets you incorporate any pre-existing Torch, Jax, or Flax
 module as a standard Keras layer by using the appropriate wrapper,
 letting you build atop existing projects with Keras. For example, train
-a Torch model using the Keras high-level training (`compile()` +
+a Torch model using the Keras high-level training API (`compile()` +
 `fit()`), or include a Flax module as a component of a larger Keras
-model. The new multi-backend support lets you use Keras a la carte.
+model. The new multi-backend support lets you use Keras à la carte.
 
 ### The 'Ops' family
 
-`keras3` introduces a new "Operations" family of function. The Ops
+`{keras3}` introduces a new "Operations" family of function. The Ops
 family, currently with over [200
 functions](https://keras.posit.co/reference/index.html#operations),
 provides a comprehensive suite of operations typically needed when
 operating on nd-arrays for deep learning. The Operation family
 supersedes and greatly expands on the former family of backend functions
-prefixed with `k_` in the `keras` package.
+prefixed with `k_` in the `{keras}` package.
 
 The Ops functions let you write backend-agnostic code. They provide a
 uniform API, regardless of if you're working with TensorFlow Tensors,
@@ -215,12 +215,13 @@ serving.
     -   `save_model_config()` / `load_model_config()`:\
         save just the model architecture as a json file.
 
--   `register_keras_serializable()`: Registering custom objects to
-    enable them to be serialized and deserialized.
+-   `register_keras_serializable()`:\
+    Register custom objects to enable them to be serialized and
+    deserialized.
 
--   `serialize_keras_object()` / `deserialize_keras_object()`: Convert
-    any Keras object as an R list of simple types that is safe to
-    convert to JSON or rds.
+-   `serialize_keras_object()` / `deserialize_keras_object()`:\
+    Convert any Keras object to an R list of simple types that is safe
+    to convert to JSON or rds.
 
 -   See the new [Serialization and Saving
     vignette](https://keras.posit.co/articles/serialization_and_saving.html)
@@ -245,7 +246,7 @@ for example usage.
 
 -   New and improved `print(model)` and `plot(model)` method. See some
     examples of output in the [Functional API
-    guide](https://keras.posit.co/articles/functional_api.html#extract-and-reuse-nodes-in-the-graph-of-layers)
+    guide](https://keras.posit.co/articles/functional_api.html)
 
 -   All new `fit()` progress bar and live metrics viewer output,
     including new dark-mode support in the RStudio IDE.
@@ -283,10 +284,10 @@ away.
 
 If you have legacy code that uses `{keras}`, you are encouraged to
 update the code for `{keras3}`. For many high-level API functions, such
-as **`layer_dense()`**, **`fit()`**, and **`keras_model()`**, minimal to
-no changes are required. However there is a long tail of small changes
-that you might need to make when updating code that made use of the
-lower-level Keras API. Some of those are documented here:
+as `layer_dense()`, `fit()`, and `keras_model()`, minimal to no changes
+are required. However there is a long tail of small changes that you
+might need to make when updating code that made use of the lower-level
+Keras API. Some of those are documented here:
 <https://keras.io/guides/migrating_to_keras_3/>.
 
 If you're running into issues or have questions about updating, don't