balkian/sitc
1
0
Fork 0
mirror of https://github.com/gsi-upm/sitc synced 2024-12-22 03:38:13 +00:00
Code Issues Releases Wiki Activity

Typo

Browse Source
This commit is contained in:
cif2cif 2016-03-29 12:57:26 +02:00
parent e443d5442c
commit 57afdae23e
2 changed files with 2 additions and 2 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
ml2/3_0_0_Intro_ML_2.ipynb
View File

@ -27,7 +27,7 @@
"source": [
"# Introduction to Machine Learning II\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 the machine learning algorithm 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, analyzing 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",
"# Objectives\n",
"\n",

2
ml2/3_4_Visualisation_Pandas.ipynb
View File

@ -4730,7 +4730,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Feature Engineering is the process of using domain/expert knowledge of the data to create features that make machine learning algorithms work better. We are going to define several [new ones](https://triangleinequality.wordpress.com/2013/09/08/basic-feature-engineering-with-the-titanic-data/)."
"Feature Engineering is the process of using domain/expert knowledge of the data to create features that make machine learning algorithms work better. We are going to define several [new ones](https://triangleinequality.wordpress.com/2013/09/08/basic-feature-engineering-with-the-titanic-data/) in the exercise."
]
},
{