{ "cells": [ { "cell_type": "markdown", "id": "56fc210f-fd9c-4114-8e1f-4f6a62fbc846", "metadata": {}, "source": [ "# Linear Regression with TensorFlow\n", "\n", "In a regression problem, the aim is to predict the output of a continuous value, like a price or a probability. Contrast this with a classification problem, where the aim is to select a class from a list of classes (for example, where a picture contains an apple or an orange, recognizing which fruit is in the picture).\n", "\n", "This tutorial uses the classic [Auto (miles per galon) MPG](https://archive.ics.uci.edu/ml/datasets/auto+mpg) dataset and demonstrates how to build models to predict the fuel efficiency of the late-1970s and early 1980s automobiles. To do this, you will provide the models with a description of many automobiles from that time period. This description includes attributes like cylinders, displacement, horsepower, and weight.\n", "\n", "This example uses the Keras API. (Visit the Keras tutorials and guides to learn more.)\n", "\n", "```{contents}\n", ":local:\n", "```" ] }, { "cell_type": "code", "execution_count": 1, "id": "f465c6c0-fba3-4f79-9c6f-f83b7c952b73", "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt\n", "import numpy as np\n", "import pandas as pd\n", "import seaborn as sns\n", "import tensorflow as tf\n", "from tensorflow import keras\n", "from tensorflow.keras import layers\n", "\n", "# Make NumPy printouts easier to read.\n", "np.set_printoptions(precision=3, suppress=True)" ] }, { "cell_type": "code", "execution_count": 2, "id": "99de2795-e77d-4d2b-8d7c-0c40ccfe38de", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "2.17.0\n" ] } ], "source": [ "print(tf.__version__)" ] }, { "cell_type": "markdown", "id": "881f91d1-5711-4b5e-a4d9-357560707e28", "metadata": {}, "source": [ "## Dataset\n", "\n", "The dataset is available from the [UCI Machine Learning Repository](https://archive.ics.uci.edu/ml/)." ] }, { "cell_type": "code", "execution_count": 3, "id": "410b353c-5401-4c23-ba56-bb8fbfe17ce1", "metadata": {}, "outputs": [], "source": [ "url = \"http://archive.ics.uci.edu/ml/machine-learning-databases/auto-mpg/auto-mpg.data\"\n", "column_names = [\n", " \"MPG\",\n", " \"Cylinders\",\n", " \"Displacement\",\n", " \"Horsepower\",\n", " \"Weight\",\n", " \"Acceleration\",\n", " \"Model Year\",\n", " \"Origin\",\n", "]\n", "\n", "raw_dataset = pd.read_csv(\n", " url, names=column_names, na_values=\"?\", comment=\"\\t\", sep=\" \", skipinitialspace=True\n", ")" ] }, { "cell_type": "code", "execution_count": 4, "id": "359f9aea-a524-47c5-8a8d-6395b85d6d31", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " MPG Cylinders Displacement Horsepower Weight Acceleration \\\n", "393 27.0 4 140.0 86.0 2790.0 15.6 \n", "394 44.0 4 97.0 52.0 2130.0 24.6 \n", "395 32.0 4 135.0 84.0 2295.0 11.6 \n", "396 28.0 4 120.0 79.0 2625.0 18.6 \n", "397 31.0 4 119.0 82.0 2720.0 19.4 \n", "\n", " Model Year Origin \n", "393 82 1 \n", "394 82 2 \n", "395 82 1 \n", "396 82 1 \n", "397 82 1 " ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "dataset = raw_dataset.copy()\n", "dataset.tail()" ] }, { "cell_type": "markdown", "id": "1df9d95c-8cd7-4fe3-8972-d00f06da8f7b", "metadata": {}, "source": [ "### Clean the data" ] }, { "cell_type": "code", "execution_count": 5, "id": "7c33acb8-2995-48c6-943e-0f5dc65a7c5c", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "MPG 0\n", "Cylinders 0\n", "Displacement 0\n", "Horsepower 6\n", "Weight 0\n", "Acceleration 0\n", "Model Year 0\n", "Origin 0\n", "dtype: int64" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# The dataset contains a few unknown values\n", "dataset.isna().sum()" ] }, { "cell_type": "code", "execution_count": 6, "id": "008c88ba-3285-491e-8662-643f49edb3d0", "metadata": {}, "outputs": [], "source": [ "# Drop those rows to keep this initial tutorial simple\n", "dataset = dataset.dropna()" ] }, { "cell_type": "code", "execution_count": 7, "id": "4c0c1702-72d8-4abc-9d3d-099d59f7ebe7", "metadata": {}, "outputs": [], "source": [ "# One-hot encoding Origin column\n", "dataset[\"Origin\"] = dataset[\"Origin\"].map({1: \"USA\", 2: \"Europe\", 3: \"Japan\"})" ] }, { "cell_type": "code", "execution_count": 8, "id": "0ff0bf10-897d-4a19-82ba-3196f73053d4", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " MPG Cylinders Displacement Horsepower Weight Acceleration \\\n", "393 27.0 4 140.0 86.0 2790.0 15.6 \n", "394 44.0 4 97.0 52.0 2130.0 24.6 \n", "395 32.0 4 135.0 84.0 2295.0 11.6 \n", "396 28.0 4 120.0 79.0 2625.0 18.6 \n", "397 31.0 4 119.0 82.0 2720.0 19.4 \n", "\n", " Model Year Europe Japan USA \n", "393 82 False False True \n", "394 82 True False False \n", "395 82 False False True \n", "396 82 False False True \n", "397 82 False False True " ] }, "execution_count": 8, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# The \"Origin\" column is categorical, not numeric.\n", "# So the next step is to one-hot encode the values in the column with pd.get_dummies.\n", "# https://pandas.pydata.org/docs/reference/api/pandas.get_dummies.html\n", "\n", "dataset = pd.get_dummies(dataset, columns=[\"Origin\"], prefix=\"\", prefix_sep=\"\")\n", "dataset.tail()" ] }, { "cell_type": "markdown", "id": "c599b0c0-4e1f-43f9-9581-57290c017346", "metadata": {}, "source": [ "### Split the data into training and test sets" ] }, { "cell_type": "code", "execution_count": 9, "id": "259196e6-2344-4bb0-9725-dfa9575ce48a", "metadata": {}, "outputs": [], "source": [ "train_dataset = dataset.sample(frac=0.8, random_state=0)\n", "test_dataset = dataset.drop(train_dataset.index)" ] }, { "cell_type": "markdown", "id": "2eeee04e-e7d9-4244-9953-3198a3086c7f", "metadata": {}, "source": [ "### Inspect the data\n", "\n", "Review the joint distribution of a few pairs of columns from the training set.\n", "\n", "The top row suggests that the fuel efficiency (MPG) is a function of all the other parameters. The other rows indicate they are functions of each other." ] }, { "cell_type": "code", "execution_count": 10, "id": "1f2b4a97-ec7c-4a78-8ea8-31ddf2df2597", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 10, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sns.pairplot(\n", " train_dataset[[\"MPG\", \"Cylinders\", \"Displacement\", \"Weight\"]], diag_kind=\"kde\"\n", ")" ] }, { "cell_type": "code", "execution_count": 11, "id": "97164796-da20-453c-b195-fa92cf3e3da3", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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countmeanstdmin25%50%75%max
MPG314.023.3105107.72865210.017.0022.028.9546.6
Cylinders314.05.4777071.6997883.04.004.08.008.0
Displacement314.0195.318471104.33158968.0105.50151.0265.75455.0
Horsepower314.0104.86942738.09621446.076.2594.5128.00225.0
Weight314.02990.251592843.8985961649.02256.502822.53608.005140.0
Acceleration314.015.5592362.7892308.013.8015.517.2024.8
Model Year314.075.8980893.67564270.073.0076.079.0082.0
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" ], "text/plain": [ " count mean std min 25% 50% \\\n", "MPG 314.0 23.310510 7.728652 10.0 17.00 22.0 \n", "Cylinders 314.0 5.477707 1.699788 3.0 4.00 4.0 \n", "Displacement 314.0 195.318471 104.331589 68.0 105.50 151.0 \n", "Horsepower 314.0 104.869427 38.096214 46.0 76.25 94.5 \n", "Weight 314.0 2990.251592 843.898596 1649.0 2256.50 2822.5 \n", "Acceleration 314.0 15.559236 2.789230 8.0 13.80 15.5 \n", "Model Year 314.0 75.898089 3.675642 70.0 73.00 76.0 \n", "\n", " 75% max \n", "MPG 28.95 46.6 \n", "Cylinders 8.00 8.0 \n", "Displacement 265.75 455.0 \n", "Horsepower 128.00 225.0 \n", "Weight 3608.00 5140.0 \n", "Acceleration 17.20 24.8 \n", "Model Year 79.00 82.0 " ] }, "execution_count": 11, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Let's also check the overall statistics. Note how each feature covers a very different range\n", "train_dataset.describe().transpose()" ] }, { "cell_type": "markdown", "id": "a3c43735-939b-4b22-9d47-620663545ee3", "metadata": {}, "source": [ "### Split features from labels" ] }, { "cell_type": "code", "execution_count": 12, "id": "4a52e26a-ce32-4dd0-a36f-3a904b96ecfa", "metadata": {}, "outputs": [], "source": [ "train_features = train_dataset.copy()\n", "test_features = test_dataset.copy()\n", "\n", "train_labels = train_features.pop(\"MPG\")\n", "test_labels = test_features.pop(\"MPG\")" ] }, { "cell_type": "markdown", "id": "aeaed497-1db5-41ed-a174-e2b893b72e06", "metadata": {}, "source": [ "## Normalization\n", "\n", "In the table of statistics it's easy to see how different the ranges of each feature are.\n", "\n", "It is good practice to normalize features that use different scales and ranges.\n", "\n", "One reason this is important is because the features are multiplied by the model weights. So, the scale of the outputs and the scale of the gradients are affected by the scale of the inputs.\n", "\n", "Although a model might converge without feature normalization, normalization makes training much more stable." ] }, { "cell_type": "code", "execution_count": 13, "id": "1ce6e29c-70e0-4c5f-8c78-a9309dbdddea", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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meanstd
MPG23.3105107.728652
Cylinders5.4777071.699788
Displacement195.318471104.331589
Horsepower104.86942738.096214
Weight2990.251592843.898596
Acceleration15.5592362.789230
Model Year75.8980893.675642
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" ], "text/plain": [ " mean std\n", "MPG 23.310510 7.728652\n", "Cylinders 5.477707 1.699788\n", "Displacement 195.318471 104.331589\n", "Horsepower 104.869427 38.096214\n", "Weight 2990.251592 843.898596\n", "Acceleration 15.559236 2.789230\n", "Model Year 75.898089 3.675642" ] }, "execution_count": 13, "metadata": {}, "output_type": "execute_result" } ], "source": [ "train_dataset.describe().transpose()[[\"mean\", \"std\"]]" ] }, { "cell_type": "code", "execution_count": 14, "id": "9c4ecc15-3cc0-46e6-a386-4b5fc5445a1a", "metadata": {}, "outputs": [], "source": [ "normalizer = tf.keras.layers.Normalization(axis=-1)" ] }, { "cell_type": "code", "execution_count": 15, "id": "3ec2673b-9ce7-4b3f-90b8-283b794c1acb", "metadata": {}, "outputs": [], "source": [ "normalizer.adapt(np.array(train_features))" ] }, { "cell_type": "code", "execution_count": 16, "id": "154bb1c6-dd79-487e-a8dc-fee62b71439c", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "[[ 5.478 195.318 104.869 2990.252 15.559 75.898 0.178 0.197\n", " 0.624]]\n" ] } ], "source": [ "print(normalizer.mean.numpy())" ] }, { "cell_type": "code", "execution_count": 17, "id": "ae601ac4-15c8-4fab-8a39-f37f1f299c3e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "First example: [[4 90.0 75.0 2125.0 14.5 74 False False True]]\n", "\n", "Normalized: [[-0.87 -1.01 -0.79 -1.03 -0.38 -0.52 -0.47 -0.5 0.78]]\n" ] } ], "source": [ "first = np.array(train_features[:1])\n", "\n", "with np.printoptions(precision=2, suppress=True):\n", " print(\"First example:\", first)\n", " print()\n", " print(\"Normalized:\", normalizer(np.asarray(first).astype(np.float32)).numpy())" ] }, { "cell_type": "markdown", "id": "324c1445-7b2f-4d14-bf91-7e1a226ab2ab", "metadata": {}, "source": [ "## Linear regression" ] }, { "cell_type": "markdown", "id": "67100c25-6e04-4497-b34c-9d470d4204b5", "metadata": {}, "source": [ "### Linear regression with one variable\n", "\n", "Begin with a single-variable linear regression to predict 'MPG' from 'Horsepower'.\n", "\n", "Training a model with tf.keras typically starts by defining the model architecture. Use a tf.keras.Sequential model, which represents a sequence of steps.\n", "\n", "There are two steps in your single-variable linear regression model:\n", "\n", "* Normalize the 'Horsepower' input features using the tf.keras.layers.Normalization preprocessing layer.\n", "* Apply a linear transformation (y = mx + b) to produce 1 output using a linear layer (tf.keras.layers.Dense).\n", "\n", "The number of inputs can either be set by the input_shape argument, or automatically when the model is run for the first time." ] }, { "cell_type": "code", "execution_count": 18, "id": "64bb1e9e-2193-4c5f-a737-99e8e5b155a3", "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "/Users/ariefrahmansyah/Library/Caches/pypoetry/virtualenvs/applied-python-training-MLD32oJZ-py3.12/lib/python3.12/site-packages/keras/src/layers/preprocessing/tf_data_layer.py:19: UserWarning: Do not pass an `input_shape`/`input_dim` argument to a layer. When using Sequential models, prefer using an `Input(shape)` object as the first layer in the model instead.\n", " super().__init__(**kwargs)\n" ] } ], "source": [ "horsepower = np.array(train_features[\"Horsepower\"])\n", "\n", "horsepower_normalizer = layers.Normalization(\n", " input_shape=[\n", " 1,\n", " ],\n", " axis=None,\n", ")\n", "horsepower_normalizer.adapt(horsepower)" ] }, { "cell_type": "code", "execution_count": 19, "id": "6eccbc14-c7a3-476f-9029-b101bdd5f0c8", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Model: \"sequential\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃ Layer (type)                     Output Shape                  Param # ┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ normalization_1 (Normalization) │ (None, 1)              │             3 │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense (Dense)                   │ (None, 1)              │             2 │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
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 Trainable params: 2 (8.00 B)\n",
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lossval_lossepoch
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" ], "text/plain": [ " loss val_loss epoch\n", "95 3.803140 4.193005 95\n", "96 3.802998 4.194662 96\n", "97 3.803431 4.190634 97\n", "98 3.805895 4.208922 98\n", "99 3.804925 4.192336 99" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" } ], "source": [ "hist = pd.DataFrame(history.history)\n", "hist[\"epoch\"] = history.epoch\n", "hist.tail()" ] }, { "cell_type": "code", "execution_count": 24, "id": "04c59136-056b-41b3-bda8-0a4c759a0c5b", "metadata": {}, "outputs": [], "source": [ "def plot_loss(history):\n", " plt.plot(history.history[\"loss\"], label=\"loss\")\n", " plt.plot(history.history[\"val_loss\"], label=\"val_loss\")\n", " plt.ylim([0, 10])\n", " plt.xlabel(\"Epoch\")\n", " plt.ylabel(\"Error [MPG]\")\n", " plt.legend()\n", " plt.grid(True)" ] }, { "cell_type": "code", "execution_count": 25, "id": "b1cb6a04-6c01-4969-a05b-c84df16d51d1", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_loss(history)" ] }, { "cell_type": "code", "execution_count": 26, "id": "07bcca1e-4d81-4061-a8ba-48d32d6bc8eb", "metadata": {}, "outputs": [], "source": [ "# Collect the results on the test set for later\n", "test_results = {}\n", "\n", "test_results[\"horsepower_model\"] = horsepower_model.evaluate(\n", " test_features[\"Horsepower\"], test_labels, verbose=0\n", ")" ] }, { "cell_type": "code", "execution_count": 27, "id": "c97337c9-8700-4fd8-91cb-20f80e66c138", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m8/8\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 2ms/step \n" ] } ], "source": [ "# Since this is a single variable regression, it's easy to view the model's predictions as a function of the input\n", "x = tf.linspace(0.0, 250, 251)\n", "y = horsepower_model.predict(x)" ] }, { "cell_type": "code", "execution_count": 28, "id": "bdebfc46-aa2f-41e3-a0b8-37b72b8011e3", "metadata": {}, "outputs": [], "source": [ "def plot_horsepower(x, y):\n", " plt.scatter(train_features[\"Horsepower\"], train_labels, label=\"Data\")\n", " plt.plot(x, y, color=\"k\", label=\"Predictions\")\n", " plt.xlabel(\"Horsepower\")\n", " plt.ylabel(\"MPG\")\n", " plt.legend()" ] }, { "cell_type": "code", "execution_count": 29, "id": "b27f0c29-4cf5-4f6f-8b63-5b0e4f9cf64d", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_horsepower(x, y)" ] }, { "cell_type": "markdown", "id": "bed58710-c023-40ce-a45f-4f2d94e96e1c", "metadata": {}, "source": [ "### Linear regression with multiple inputs\n", "\n", "You can use an almost identical setup to make predictions based on multiple inputs. This model still does the same y = mx + b, except that m is a matrix and b is a vector.\n", "\n", "Create a two-step Keras Sequential model again with the first layer being normalizer (tf.keras.layers.Normalization(axis=-1)) you defined earlier and adapted to the whole dataset:" ] }, { "cell_type": "code", "execution_count": 30, "id": "6705af4d-1f9b-48e3-bbf3-f7882c000ed3", "metadata": {}, "outputs": [], "source": [ "linear_model = tf.keras.Sequential([normalizer, layers.Dense(units=1)])" ] }, { "cell_type": "code", "execution_count": 31, "id": "6daeaee8-eeea-4ede-8733-f86ebccba99f", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m1/1\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 48ms/step\n" ] }, { "data": { "text/plain": [ "array([[ 0.129],\n", " [ 0.144],\n", " [ 0.7 ],\n", " [-1.14 ],\n", " [ 0.208],\n", " [ 0.223],\n", " [ 0.356],\n", " [-0.496],\n", " [ 0.84 ],\n", " [ 1.644]], dtype=float32)" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" } ], "source": [ "linear_model.predict(train_features[:10])" ] }, { "cell_type": "code", "execution_count": 32, "id": "c9a32632-c70f-4810-ae23-a0e01c4a7e39", "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 32, "metadata": {}, "output_type": "execute_result" } ], "source": [ "linear_model.layers[1].kernel" ] }, { "cell_type": "code", "execution_count": 33, "id": "42764e50-28de-43a5-910f-0686cf000ed2", "metadata": {}, "outputs": [], "source": [ "linear_model.compile(\n", " optimizer=tf.keras.optimizers.Adam(learning_rate=0.1), loss=\"mean_absolute_error\"\n", ")" ] }, { "cell_type": "code", "execution_count": 34, "id": "c95aefa9-6220-4f9f-86a7-877db3b45679", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 2.01 s, sys: 245 ms, total: 2.25 s\n", "Wall time: 2.1 s\n" ] } ], "source": [ "%%time\n", "history = linear_model.fit(\n", " train_features,\n", " train_labels,\n", " epochs=100,\n", " # Suppress logging.\n", " verbose=0,\n", " # Calculate validation results on 20% of the training data.\n", " validation_split=0.2,\n", ")" ] }, { "cell_type": "code", "execution_count": 35, "id": "35fce4fe-1374-4083-b445-2e6fcb7cb0f0", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_loss(history)" ] }, { "cell_type": "code", "execution_count": 36, "id": "6154fe66-5cbd-47e4-82a0-cd028224cdb7", "metadata": {}, "outputs": [], "source": [ "test_results[\"linear_model\"] = linear_model.evaluate(\n", " test_features, test_labels, verbose=0\n", ")" ] }, { "cell_type": "markdown", "id": "aa59face-b7d6-4c7d-8e0a-98d2e78a96de", "metadata": {}, "source": [ "## Regression with a deep neural network\n", "\n", "In the previous section, you implemented two linear models for single and multiple inputs.\n", "\n", "Here, you will implement single-input and multiple-input DNN models.\n", "\n", "The code is basically the same except the model is expanded to include some \"hidden\" non-linear layers. The name \"hidden\" here just means not directly connected to the inputs or outputs.\n", "\n", "These models will contain a few more layers than the linear model:\n", "\n", "* The normalization layer, as before (with horsepower_normalizer for a single-input model and normalizer for a multiple-input model).\n", "* Two hidden, non-linear, Dense layers with the ReLU (relu) activation function nonlinearity.\n", "* A linear Dense single-output layer." ] }, { "cell_type": "code", "execution_count": 37, "id": "9710f0ea-b08d-46ab-87ac-25aaefb8e01b", "metadata": {}, "outputs": [], "source": [ "def build_and_compile_model(norm):\n", " model = keras.Sequential(\n", " [\n", " norm,\n", " layers.Dense(64, activation=\"relu\"),\n", " layers.Dense(64, activation=\"relu\"),\n", " layers.Dense(1),\n", " ]\n", " )\n", "\n", " model.compile(loss=\"mean_absolute_error\", optimizer=tf.keras.optimizers.Adam(0.001))\n", " return model" ] }, { "cell_type": "markdown", "id": "d38d3df7-20b5-4e13-aed3-0cc73e660568", "metadata": {}, "source": [ "### Regression using a DNN and a single input" ] }, { "cell_type": "code", "execution_count": 38, "id": "0a94d334-97a4-48d7-b59e-5980ce72c139", "metadata": {}, "outputs": [], "source": [ "dnn_horsepower_model = build_and_compile_model(horsepower_normalizer)" ] }, { "cell_type": "code", "execution_count": 39, "id": "3bacf1ab-3828-4979-b60e-388c08d45229", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Model: \"sequential_2\"\n",
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┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃ Layer (type)                     Output Shape                  Param # ┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ normalization_1 (Normalization) │ (None, 1)              │             3 │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_2 (Dense)                 │ (None, 64)             │           128 │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_3 (Dense)                 │ (None, 64)             │         4,160 │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_4 (Dense)                 │ (None, 1)              │            65 │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "
\n" ], "text/plain": [ "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", "│ normalization_1 (\u001b[38;5;33mNormalization\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m3\u001b[0m │\n", "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", "│ dense_2 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m128\u001b[0m │\n", "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", "│ dense_3 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m64\u001b[0m) │ \u001b[38;5;34m4,160\u001b[0m │\n", "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", "│ dense_4 (\u001b[38;5;33mDense\u001b[0m) │ (\u001b[38;5;45mNone\u001b[0m, \u001b[38;5;34m1\u001b[0m) │ \u001b[38;5;34m65\u001b[0m │\n", "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
 Total params: 4,356 (17.02 KB)\n",
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 Trainable params: 4,353 (17.00 KB)\n",
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 Non-trainable params: 3 (16.00 B)\n",
       "
\n" ], "text/plain": [ "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m3\u001b[0m (16.00 B)\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dnn_horsepower_model.summary()" ] }, { "cell_type": "code", "execution_count": 40, "id": "12eae944-1317-4389-a5dc-1dfcb3c421fb", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 2.2 s, sys: 259 ms, total: 2.46 s\n", "Wall time: 2.18 s\n" ] } ], "source": [ "%%time\n", "history = dnn_horsepower_model.fit(\n", " train_features[\"Horsepower\"],\n", " train_labels,\n", " validation_split=0.2,\n", " verbose=0,\n", " epochs=100,\n", ")" ] }, { "cell_type": "code", "execution_count": 41, "id": "7b700471-6147-4b81-90f8-ff4cd9b56f99", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_loss(history)" ] }, { "cell_type": "code", "execution_count": 42, "id": "57c2e67c-1db5-4834-a2d4-43fdc3a3cd6a", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "WARNING:tensorflow:5 out of the last 11 calls to .one_step_on_data_distributed at 0x302b19ee0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n", "\u001b[1m1/8\u001b[0m \u001b[32m━━\u001b[0m\u001b[37m━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m0s\u001b[0m 32ms/stepWARNING:tensorflow:5 out of the last 17 calls to .one_step_on_data_distributed at 0x302b19ee0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has reduce_retracing=True option that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for more details.\n", "\u001b[1m8/8\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 3ms/step \n" ] } ], "source": [ "x = tf.linspace(0.0, 250, 251)\n", "y = dnn_horsepower_model.predict(x)" ] }, { "cell_type": "code", "execution_count": 43, "id": "6778aabd-08cd-4c7f-9461-b5e46b0430ef", "metadata": {}, "outputs": [ { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_horsepower(x, y)" ] }, { "cell_type": "code", "execution_count": 44, "id": "92997271-03c7-4c46-a3f6-ff86fbd436fa", "metadata": {}, "outputs": [], "source": [ "test_results[\"dnn_horsepower_model\"] = dnn_horsepower_model.evaluate(\n", " test_features[\"Horsepower\"], test_labels, verbose=0\n", ")" ] }, { "cell_type": "markdown", "id": "3757d6f2-a82c-4338-9728-59ef51be5ce3", "metadata": {}, "source": [ "### Regression using a DNN and multiple inputs" ] }, { "cell_type": "code", "execution_count": 45, "id": "74c48953-246e-4ab8-a8da-e6eba1267e01", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
Model: \"sequential_3\"\n",
       "
\n" ], "text/plain": [ "\u001b[1mModel: \"sequential_3\"\u001b[0m\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n",
       "┃ Layer (type)                     Output Shape                  Param # ┃\n",
       "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n",
       "│ normalization (Normalization)   │ (10, 9)                │            19 │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_5 (Dense)                 │ ?                      │   0 (unbuilt) │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_6 (Dense)                 │ ?                      │   0 (unbuilt) │\n",
       "├─────────────────────────────────┼────────────────────────┼───────────────┤\n",
       "│ dense_7 (Dense)                 │ ?                      │   0 (unbuilt) │\n",
       "└─────────────────────────────────┴────────────────────────┴───────────────┘\n",
       "
\n" ], "text/plain": [ "┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━┓\n", "┃\u001b[1m \u001b[0m\u001b[1mLayer (type) \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1mOutput Shape \u001b[0m\u001b[1m \u001b[0m┃\u001b[1m \u001b[0m\u001b[1m Param #\u001b[0m\u001b[1m \u001b[0m┃\n", "┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━┩\n", "│ normalization (\u001b[38;5;33mNormalization\u001b[0m) │ (\u001b[38;5;34m10\u001b[0m, \u001b[38;5;34m9\u001b[0m) │ \u001b[38;5;34m19\u001b[0m │\n", "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", "│ dense_5 (\u001b[38;5;33mDense\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", "│ dense_6 (\u001b[38;5;33mDense\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", "├─────────────────────────────────┼────────────────────────┼───────────────┤\n", "│ dense_7 (\u001b[38;5;33mDense\u001b[0m) │ ? │ \u001b[38;5;34m0\u001b[0m (unbuilt) │\n", "└─────────────────────────────────┴────────────────────────┴───────────────┘\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
 Total params: 19 (80.00 B)\n",
       "
\n" ], "text/plain": [ "\u001b[1m Total params: \u001b[0m\u001b[38;5;34m19\u001b[0m (80.00 B)\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
 Trainable params: 0 (0.00 B)\n",
       "
\n" ], "text/plain": [ "\u001b[1m Trainable params: \u001b[0m\u001b[38;5;34m0\u001b[0m (0.00 B)\n" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "
 Non-trainable params: 19 (80.00 B)\n",
       "
\n" ], "text/plain": [ "\u001b[1m Non-trainable params: \u001b[0m\u001b[38;5;34m19\u001b[0m (80.00 B)\n" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "dnn_model = build_and_compile_model(normalizer)\n", "dnn_model.summary()" ] }, { "cell_type": "code", "execution_count": 46, "id": "6ae17f92-1417-452e-aadb-0a5fd25690b9", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "CPU times: user 2.2 s, sys: 253 ms, total: 2.45 s\n", "Wall time: 2.17 s\n" ] } ], "source": [ "%%time\n", "history = dnn_model.fit(\n", " train_features, train_labels, validation_split=0.2, verbose=0, epochs=100\n", ")" ] }, { "cell_type": "code", "execution_count": 47, "id": "2dbb0edd-e161-499c-b411-7322990e410e", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plot_loss(history)" ] }, { "cell_type": "code", "execution_count": 48, "id": "dfb89f73-7b06-488a-aee7-f1023ff9b973", "metadata": {}, "outputs": [], "source": [ "test_results[\"dnn_model\"] = dnn_model.evaluate(test_features, test_labels, verbose=0)" ] }, { "cell_type": "markdown", "id": "4777f059-f8a2-47ac-aec2-1b667a8fc90d", "metadata": {}, "source": [ "## Performance" ] }, { "cell_type": "code", "execution_count": 49, "id": "06ddacfe-a8b7-459e-8b2d-1a1c989460e6", "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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Mean absolute error [MPG]
horsepower_model3.653414
linear_model2.462059
dnn_horsepower_model2.895719
dnn_model1.662322
\n", "
" ], "text/plain": [ " Mean absolute error [MPG]\n", "horsepower_model 3.653414\n", "linear_model 2.462059\n", "dnn_horsepower_model 2.895719\n", "dnn_model 1.662322" ] }, "execution_count": 49, "metadata": {}, "output_type": "execute_result" } ], "source": [ "pd.DataFrame(test_results, index=[\"Mean absolute error [MPG]\"]).T" ] }, { "cell_type": "markdown", "id": "3770ffe3-2d67-466e-98ce-6ba43909b860", "metadata": {}, "source": [ "### Make predictions" ] }, { "cell_type": "code", "execution_count": 50, "id": "8f5f2698-7964-457e-92e5-4afbe5c3b78e", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[1m3/3\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 7ms/step \n" ] }, { "data": { "image/png": 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "test_predictions = dnn_model.predict(test_features).flatten()\n", "\n", "a = plt.axes(aspect=\"equal\")\n", "plt.scatter(test_labels, test_predictions)\n", "plt.xlabel(\"True Values [MPG]\")\n", "plt.ylabel(\"Predictions [MPG]\")\n", "lims = [0, 50]\n", "plt.xlim(lims)\n", "plt.ylim(lims)\n", "_ = plt.plot(lims, lims)" ] }, { "cell_type": "code", "execution_count": 51, "id": "058dfbc9-26df-4f15-9fe8-eccd513dab72", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "error = test_predictions - test_labels\n", "plt.hist(error, bins=25)\n", "plt.xlabel(\"Prediction Error [MPG]\")\n", "_ = plt.ylabel(\"Count\")" ] }, { "cell_type": "code", "execution_count": null, "id": "2ce5c19f-7aa6-4305-b4c7-03d93fed5683", "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.12.4" } }, "nbformat": 4, "nbformat_minor": 5 }