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+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
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+ " ----------- ---------------------------- 90.1/300.9 MB 4.9 MB/s eta 0:00:43\n",
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+ " ------------ --------------------------- 91.6/300.9 MB 4.8 MB/s eta 0:00:44\n",
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+ " ------------ --------------------------- 92.9/300.9 MB 4.3 MB/s eta 0:00:48\n",
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+ " ------------ --------------------------- 93.3/300.9 MB 4.2 MB/s eta 0:00:50\n",
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+ " ------------ --------------------------- 93.7/300.9 MB 4.2 MB/s eta 0:00:50\n",
+ " ------------ --------------------------- 93.8/300.9 MB 4.1 MB/s eta 0:00:50\n",
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+ " ------------ --------------------------- 94.2/300.9 MB 4.1 MB/s eta 0:00:51\n",
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+ " ------------ --------------------------- 94.6/300.9 MB 4.1 MB/s eta 0:00:51\n",
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+ " ------------ --------------------------- 95.2/300.9 MB 4.0 MB/s eta 0:00:52\n",
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+ " ------------ --------------------------- 95.6/300.9 MB 4.0 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 95.8/300.9 MB 4.0 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 96.0/300.9 MB 3.9 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 96.3/300.9 MB 4.0 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 96.5/300.9 MB 4.0 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 96.7/300.9 MB 4.0 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 97.0/300.9 MB 4.0 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 97.1/300.9 MB 4.0 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 97.3/300.9 MB 4.0 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 97.5/300.9 MB 3.9 MB/s eta 0:00:52\n",
+ " ------------ --------------------------- 97.7/300.9 MB 3.9 MB/s eta 0:00:52\n",
+ " ------------- -------------------------- 97.8/300.9 MB 3.9 MB/s eta 0:00:52\n",
+ " ------------- -------------------------- 98.0/300.9 MB 3.9 MB/s eta 0:00:53\n",
+ " ------------- -------------------------- 98.1/300.9 MB 3.9 MB/s eta 0:00:53\n",
+ " ------------- -------------------------- 98.2/300.9 MB 3.8 MB/s eta 0:00:53\n",
+ " ------------- -------------------------- 98.3/300.9 MB 3.8 MB/s eta 0:00:54\n",
+ " ------------- -------------------------- 98.5/300.9 MB 3.8 MB/s eta 0:00:54\n",
+ " ------------- -------------------------- 98.6/300.9 MB 3.7 MB/s eta 0:00:55\n",
+ " ------------- -------------------------- 98.8/300.9 MB 3.7 MB/s eta 0:00:55\n",
+ " ------------- -------------------------- 98.9/300.9 MB 3.7 MB/s eta 0:00:55\n",
+ " ------------- -------------------------- 99.0/300.9 MB 3.7 MB/s eta 0:00:55\n",
+ " ------------- -------------------------- 99.2/300.9 MB 3.7 MB/s eta 0:00:56\n",
+ " ------------- -------------------------- 99.3/300.9 MB 3.6 MB/s eta 0:00:56\n",
+ " ------------- -------------------------- 99.5/300.9 MB 3.6 MB/s eta 0:00:56\n",
+ " ------------- -------------------------- 99.7/300.9 MB 3.6 MB/s eta 0:00:56\n",
+ " ------------- -------------------------- 99.8/300.9 MB 3.6 MB/s eta 0:00:56\n",
+ " ------------- -------------------------- 100.0/300.9 MB 3.6 MB/s eta 0:00:56\n",
+ " ------------- -------------------------- 100.2/300.9 MB 3.6 MB/s eta 0:00:56\n",
+ " ------------- -------------------------- 100.3/300.9 MB 3.6 MB/s eta 0:00:57\n",
+ " ------------- -------------------------- 100.5/300.9 MB 3.5 MB/s eta 0:00:57\n",
+ " ------------- -------------------------- 100.6/300.9 MB 3.5 MB/s eta 0:00:57\n",
+ " ------------- -------------------------- 100.7/300.9 MB 3.5 MB/s eta 0:00:57\n",
+ " ------------- -------------------------- 100.9/300.9 MB 3.5 MB/s eta 0:00:58\n",
+ " ------------- -------------------------- 101.0/300.9 MB 3.5 MB/s eta 0:00:58\n",
+ " ------------- -------------------------- 101.2/300.9 MB 3.5 MB/s eta 0:00:58\n",
+ " ------------- -------------------------- 101.4/300.9 MB 3.4 MB/s eta 0:00:58\n",
+ " ------------- -------------------------- 101.5/300.9 MB 3.4 MB/s eta 0:00:58\n",
+ " ------------- -------------------------- 101.6/300.9 MB 3.4 MB/s eta 0:00:59\n",
+ " ------------- -------------------------- 101.6/300.9 MB 3.4 MB/s eta 0:01:00\n",
+ " ------------- -------------------------- 101.7/300.9 MB 3.3 MB/s eta 0:01:00\n",
+ " ------------- -------------------------- 101.8/300.9 MB 3.3 MB/s eta 0:01:00\n",
+ " ------------- -------------------------- 101.8/300.9 MB 3.3 MB/s eta 0:01:01\n",
+ " ------------- -------------------------- 101.9/300.9 MB 3.3 MB/s eta 0:01:01\n",
+ " ------------- -------------------------- 102.0/300.9 MB 3.2 MB/s eta 0:01:02\n",
+ " ------------- -------------------------- 102.0/300.9 MB 3.2 MB/s eta 0:01:02\n",
+ " ------------- -------------------------- 102.1/300.9 MB 3.2 MB/s eta 0:01:03\n",
+ " ------------- -------------------------- 102.2/300.9 MB 3.2 MB/s eta 0:01:03\n",
+ " ------------- -------------------------- 102.3/300.9 MB 3.2 MB/s eta 0:01:03\n",
+ " ------------- -------------------------- 102.3/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 102.4/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 102.5/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 102.6/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 102.7/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 102.8/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 103.0/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 103.1/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 103.2/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 103.4/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 103.5/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 103.6/300.9 MB 3.1 MB/s eta 0:01:04\n",
+ " ------------- -------------------------- 103.8/300.9 MB 3.1 MB/s eta 0:01:05\n",
+ " ------------- -------------------------- 103.9/300.9 MB 3.1 MB/s eta 0:01:05\n",
+ " ------------- -------------------------- 104.0/300.9 MB 3.1 MB/s eta 0:01:05\n",
+ " ------------- -------------------------- 104.2/300.9 MB 3.1 MB/s eta 0:01:05\n",
+ " ------------- -------------------------- 104.3/300.9 MB 3.1 MB/s eta 0:01:05\n",
+ " ------------- -------------------------- 104.5/300.9 MB 3.0 MB/s eta 0:01:05\n",
+ " ------------- -------------------------- 104.7/300.9 MB 3.0 MB/s eta 0:01:05\n",
+ " ------------- -------------------------- 104.8/300.9 MB 3.0 MB/s eta 0:01:05\n",
+ " ------------- -------------------------- 105.0/300.9 MB 3.0 MB/s eta 0:01:05\n",
+ " ------------- -------------------------- 105.2/300.9 MB 3.0 MB/s eta 0:01:05\n",
+ " -------------- ------------------------- 105.4/300.9 MB 3.0 MB/s eta 0:01:05\n",
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+ " -------------- ------------------------- 106.0/300.9 MB 2.9 MB/s eta 0:01:08\n",
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+ "Using cached absl_py-2.1.0-py3-none-any.whl (133 kB)\n",
+ "Using cached flatbuffers-23.5.26-py2.py3-none-any.whl (26 kB)\n",
+ "Using cached gast-0.5.4-py3-none-any.whl (19 kB)\n",
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+ "Using cached cachetools-5.3.2-py3-none-any.whl (9.3 kB)\n",
+ "Installing collected packages: libclang, flatbuffers, termcolor, tensorflow-io-gcs-filesystem, tensorflow-estimator, tensorboard-data-server, rsa, protobuf, opt-einsum, oauthlib, ml-dtypes, keras, grpcio, google-pasta, gast, cachetools, astunparse, absl-py, requests-oauthlib, google-auth, google-auth-oauthlib, tensorboard, tensorflow-intel, tensorflow\n",
+ "Successfully installed absl-py-2.1.0 astunparse-1.6.3 cachetools-5.3.2 flatbuffers-23.5.26 gast-0.5.4 google-auth-2.28.0 google-auth-oauthlib-1.2.0 google-pasta-0.2.0 grpcio-1.60.1 keras-2.15.0 libclang-16.0.6 ml-dtypes-0.2.0 oauthlib-3.2.2 opt-einsum-3.3.0 protobuf-4.25.3 requests-oauthlib-1.3.1 rsa-4.9 tensorboard-2.15.2 tensorboard-data-server-0.7.2 tensorflow-2.15.0 tensorflow-estimator-2.15.0 tensorflow-intel-2.15.0 tensorflow-io-gcs-filesystem-0.31.0 termcolor-2.4.0\n",
+ "Note: you may need to restart the kernel to use updated packages.\n"
+ ]
+ }
+ ],
+ "source": [
+ "pip install tensorflow pandas"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Challenge 1 - Tic Tac Toe\n",
+ "\n",
+ "In this lab you will perform deep learning analysis on a dataset of playing [Tic Tac Toe](https://en.wikipedia.org/wiki/Tic-tac-toe).\n",
+ "\n",
+ "There are 9 grids in Tic Tac Toe that are coded as the following picture shows:\n",
+ "\n",
+ "\n",
+ "\n",
+ "In the first 9 columns of the dataset you can find which marks (`x` or `o`) exist in the grids. If there is no mark in a certain grid, it is labeled as `b`. The last column is `class` which tells you whether Player X (who always moves first in Tic Tac Toe) wins in this configuration. Note that when `class` has the value `False`, it means either Player O wins the game or it ends up as a draw."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Follow the steps suggested below to conduct a neural network analysis using Tensorflow and Keras. You will build a deep learning model to predict whether Player X wins the game or not.\n",
+ "\n",
+ "## Step 1: Data Engineering\n",
+ "\n",
+ "This dataset is almost in the ready-to-use state so you do not need to worry about missing values and so on. Still, some simple data engineering is needed.\n",
+ "\n",
+ "1. Read `tic-tac-toe.csv` into a dataframe.\n",
+ "1. Inspect the dataset. Determine if the dataset is reliable by eyeballing the data.\n",
+ "1. Convert the categorical values to numeric in all columns.\n",
+ "1. Separate the inputs and output.\n",
+ "1. Normalize the input data."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 69,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import pandas as pd\n",
+ "from sklearn.model_selection import train_test_split\n",
+ "from sklearn.preprocessing import LabelEncoder"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 70,
+ "metadata": {},
+ "outputs": [
+ {
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