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ml2/3_0_0_Intro_ML_2.ipynb
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@ -27,7 +27,7 @@
"source": [ "source": [
"# Introduction to Machine Learning II\n", "# Introduction to Machine Learning II\n",
" \n", " \n",
"In this lab session, we will go deeper in some aspects that were introduced in the previous session. This time we will delve into a little bit more detail about reading datasets, analysing data and selecting features. In addition, we will explore two additional machine learning algorithms: perceptron and SVM in a binary classification problem provided by the Titanic dataset.\n", "In this lab session, we will go deeper in some aspects that were introduced in the previous session. This time we will delve into a little bit more detail about reading datasets, analysing data and selecting features. In addition, we will explore the machine learning algorithm SVM in a binary classification problem provided by the Titanic dataset.\n",
"\n", "\n",
"# Objectives\n", "# Objectives\n",
"\n", "\n",
@ -37,7 +37,7 @@
"* Learn how to read data from a file or URL with pandas\n", "* Learn how to read data from a file or URL with pandas\n",
"* Learn how to use the pandas DataFrame data structure\n", "* Learn how to use the pandas DataFrame data structure\n",
"* Learn how to select features\n", "* Learn how to select features\n",
"* Understand better the Perceptron and SVM machine learning algorithms" "* Understand better and SVM machine learning algorithm"
] ]
}, },
{ {
@ -106,7 +106,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.5.1+" "version": "3.5.1"
} }
}, },
"nbformat": 4, "nbformat": 4,