Update all notebooks

harrywang · Sep 13, 2021 · 60e4956 · 60e4956
1 parent a39702b
commit 60e4956
Show file tree

Hide file tree

Showing 20 changed files with 275 additions and 241 deletions.
diff --git a/chapter02_mathematical-building-blocks.ipynb b/chapter02_mathematical-building-blocks.ipynb
@@ -383,7 +383,7 @@
     "colab_type": "text"
    },
    "source": [
-    "### Rank-3 tensors and higher-rank tensors"
+    "### Rank-3 and higher-rank tensors"
    ]
   },
   {
@@ -1028,7 +1028,7 @@
     "colab_type": "text"
    },
    "source": [
-    "### Chaining derivatives: the Backpropagation algorithm"
+    "### Chaining derivatives: The Backpropagation algorithm"
    ]
   },
   {
@@ -1055,7 +1055,7 @@
     "colab_type": "text"
    },
    "source": [
-    "#### The Gradient Tape in TensorFlow"
+    "#### The gradient tape in TensorFlow"
    ]
   },
   {
@@ -1337,7 +1337,7 @@
     "learning_rate = 1e-3\n",
     "\n",
     "def update_weights(gradients, weights):\n",
-    "    for g, w in zip(gradients, model.weights):\n",
+    "    for g, w in zip(gradients, weights):\n",
     "        w.assign_sub(g * learning_rate)"
    ]
   },
@@ -1434,7 +1434,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Chapter summary"
+    "## Summary"
    ]
   }
  ],

diff --git a/chapter03_introduction-to-keras-and-tf.ipynb b/chapter03_introduction-to-keras-and-tf.ipynb
@@ -42,7 +42,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Keras and TensorFlow: a brief history"
+    "## Keras and TensorFlow: A brief history"
    ]
   },
   {
@@ -60,7 +60,7 @@
     "colab_type": "text"
    },
    "source": [
-    "### Jupyter notebooks: the preferred way to run deep-learning experiments"
+    "### Jupyter notebooks: The preferred way to run deep-learning experiments"
    ]
   },
   {
@@ -87,7 +87,7 @@
     "colab_type": "text"
    },
    "source": [
-    "#### Installing packages with `pip`"
+    "#### Installing packages with pip"
    ]
   },
   {
@@ -114,7 +114,7 @@
     "colab_type": "text"
    },
    "source": [
-    "#### Constant tensors and Variables"
+    "#### Constant tensors and variables"
    ]
   },
   {
@@ -212,7 +212,7 @@
     "colab_type": "text"
    },
    "source": [
-    "**Creating a Variable**"
+    "**Creating a TensorFlow variable**"
    ]
   },
   {
@@ -233,7 +233,7 @@
     "colab_type": "text"
    },
    "source": [
-    "**Assigning a value to a Variable**"
+    "**Assigning a value to a TensorFlow variable**"
    ]
   },
   {
@@ -253,7 +253,7 @@
     "colab_type": "text"
    },
    "source": [
-    "**Assigning a value to a subset of a Variable**"
+    "**Assigning a value to a subset of a TensorFlow variable**"
    ]
   },
   {
@@ -273,7 +273,7 @@
     "colab_type": "text"
    },
    "source": [
-    "**Using assign_add**"
+    "**Using `assign_add`**"
    ]
   },
   {
@@ -293,7 +293,7 @@
     "colab_type": "text"
    },
    "source": [
-    "#### Tensor operations: doing math in TensorFlow"
+    "#### Tensor operations: Doing math in TensorFlow"
    ]
   },
   {
@@ -327,7 +327,7 @@
     "colab_type": "text"
    },
    "source": [
-    "#### A second look at the `GradientTape` API"
+    "#### A second look at the GradientTape API"
    ]
   },
   {
@@ -336,7 +336,7 @@
     "colab_type": "text"
    },
    "source": [
-    "**Using the GradientTape**"
+    "**Using the `GradientTape`**"
    ]
   },
   {
@@ -359,7 +359,7 @@
     "colab_type": "text"
    },
    "source": [
-    "**Using the GradientTape with constant tensor inputs**"
+    "**Using `GradientTape` with constant tensor inputs**"
    ]
   },
   {
@@ -408,7 +408,7 @@
     "colab_type": "text"
    },
    "source": [
-    "#### An end-to-end example: a linear classifier in pure TensorFlow"
+    "#### An end-to-end example: A linear classifier in pure TensorFlow"
    ]
   },
   {
@@ -430,9 +430,13 @@
    "source": [
     "num_samples_per_class = 1000\n",
     "negative_samples = np.random.multivariate_normal(\n",
-    "    mean=[0, 3], cov=[[1, 0.5],[0.5, 1]], size=num_samples_per_class)\n",
+    "    mean=[0, 3],\n",
+    "    cov=[[1, 0.5],[0.5, 1]],\n",
+    "    size=num_samples_per_class)\n",
     "positive_samples = np.random.multivariate_normal(\n",
-    "    mean=[3, 0], cov=[[1, 0.5],[0.5, 1]], size=num_samples_per_class)"
+    "    mean=[3, 0],\n",
+    "    cov=[[1, 0.5],[0.5, 1]],\n",
+    "    size=num_samples_per_class)"
    ]
   },
   {
@@ -648,7 +652,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Anatomy of a neural network: understanding core Keras APIs"
+    "## Anatomy of a neural network: Understanding core Keras APIs"
    ]
   },
   {
@@ -657,7 +661,7 @@
     "colab_type": "text"
    },
    "source": [
-    "### Layers: the building blocks of deep learning"
+    "### Layers: The building blocks of deep learning"
    ]
   },
   {
@@ -666,7 +670,16 @@
     "colab_type": "text"
    },
    "source": [
-    "#### The base `Layer` class in Keras"
+    "#### The base Layer class in Keras"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "colab_type": "text"
+   },
+   "source": [
+    "**A `Dense` layer implemented as a `Layer` subclass**"
    ]
   },
   {
@@ -720,7 +733,7 @@
     "colab_type": "text"
    },
    "source": [
-    "#### Automatic shape inference: building layers on the fly"
+    "#### Automatic shape inference: Building layers on the fly"
    ]
   },
   {
@@ -782,7 +795,7 @@
     "colab_type": "text"
    },
    "source": [
-    "### The \"compile\" step: configuring the learning process"
+    "### The \"compile\" step: Configuring the learning process"
    ]
   },
   {
@@ -827,7 +840,7 @@
     "colab_type": "text"
    },
    "source": [
-    "### Understanding the `fit` method"
+    "### Understanding the fit() method"
    ]
   },
   {
@@ -836,7 +849,7 @@
     "colab_type": "text"
    },
    "source": [
-    "**Calling `fit` with NumPy data**"
+    "**Calling `fit()` with NumPy data**"
    ]
   },
   {
@@ -872,7 +885,7 @@
     "colab_type": "text"
    },
    "source": [
-    "### Monitoring loss & metrics on validation data"
+    "### Monitoring loss and metrics on validation data"
    ]
   },
   {
@@ -881,7 +894,7 @@
     "colab_type": "text"
    },
    "source": [
-    "**Using the validation data argument**"
+    "**Using the `validation_data` argument**"
    ]
   },
   {
@@ -921,7 +934,7 @@
     "colab_type": "text"
    },
    "source": [
-    "### Inference: using a model after training"
+    "### Inference: Using a model after training"
    ]
   },
   {
@@ -942,7 +955,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Chapter summary"
+    "## Summary"
    ]
   }
  ],

diff --git a/chapter04_getting-started-with-neural-networks.ipynb b/chapter04_getting-started-with-neural-networks.ipynb
@@ -15,7 +15,7 @@
     "colab_type": "text"
    },
    "source": [
-    "# Getting started with neural networks: classification and regression"
+    "# Getting started with neural networks: Classification and regression"
    ]
   },
   {
@@ -24,7 +24,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Classifying movie reviews: a binary classification example"
+    "## Classifying movie reviews: A binary classification example"
    ]
   },
   {
@@ -445,7 +445,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Classifying newswires: a multiclass classification example"
+    "## Classifying newswires: A multiclass classification example"
    ]
   },
   {
@@ -994,7 +994,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Predicting house prices: a regression example"
+    "## Predicting house prices: A regression example"
    ]
   },
   {
@@ -1378,7 +1378,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Chapter summary"
+    "## Summary"
    ]
   }
  ],

diff --git a/chapter05_fundamentals-of-ml.ipynb b/chapter05_fundamentals-of-ml.ipynb
@@ -24,7 +24,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Generalization: the goal of machine learning"
+    "## Generalization: The goal of machine learning"
    ]
   },
   {
@@ -699,9 +699,9 @@
    },
    "outputs": [],
    "source": [
-    "from\u00a0keras\u00a0import\u00a0regularizers\n",
+    "from tensorflow.keras import regularizers\n",
     "regularizers.l1(0.001)\n",
-    "regularizers.l1_l2(l1=0.001,\u00a0l2=0.001)"
+    "regularizers.l1_l2(l1=0.001, l2=0.001)"
    ]
   },
   {
@@ -751,7 +751,7 @@
     "colab_type": "text"
    },
    "source": [
-    "## Chapter summary"
+    "## Summary"
    ]
   }
  ],