From 208a316543a4582d86a6f933f04b06d2e6b65a8b Mon Sep 17 00:00:00 2001 From: Sunny-dev <100015821+Sunny11092003@users.noreply.github.com> Date: Thu, 28 May 2026 09:05:58 +0530 Subject: [PATCH] Improve readability in Keras classification tutorial Improved the readability and beginner-friendliness of the Keras classification tutorial by fixing minor grammar issues, clarifying wording, and adding a helpful training comment. --- site/en/tutorials/keras/classification.ipynb | 9 +++++---- 1 file changed, 5 insertions(+), 4 deletions(-) diff --git a/site/en/tutorials/keras/classification.ipynb b/site/en/tutorials/keras/classification.ipynb index dee10f107c3..95211303281 100644 --- a/site/en/tutorials/keras/classification.ipynb +++ b/site/en/tutorials/keras/classification.ipynb @@ -333,7 +333,7 @@ "id": "rd0A0Iu0CaWq" }, "source": [ - "And the test set contains 10,000 images labels:" + "And the test set contains 10,000 image labels:" ] }, { @@ -444,7 +444,7 @@ "\n", "The basic building block of a neural network is the [*layer*](https://www.tensorflow.org/api_docs/python/tf/keras/layers). Layers extract representations from the data fed into them. Hopefully, these representations are meaningful for the problem at hand.\n", "\n", - "Most of deep learning consists of chaining together simple layers. Most layers, such as `tf.keras.layers.Dense`, have parameters that are learned during training." + "Most deep learning models consist of chaining together simple layers. Most layers, such as `tf.keras.layers.Dense`, have parameters that are learned during training." ] }, { @@ -529,6 +529,7 @@ }, "outputs": [], "source": [ + "# Train the neural network model\n", "model.fit(train_images, train_labels, epochs=10)" ] }, @@ -677,7 +678,7 @@ "id": "ygh2yYC972ne" }, "source": [ - "Define functions to graph the full set of 10 class predictions." + "Define functions to visualize the full set of 10 class predictions." ] }, { @@ -860,7 +861,7 @@ "id": "EQ5wLTkcCaXY" }, "source": [ - "Now predict the correct label for this image:" + "Now predict the label for this image:" ] }, {