R – Machine Learning

These slides give an introduction to ROC curves.

In this article I analyse all US president inauguration speeches in terms of sentiment, length of sentences, party of the president and length of speech. All these information will be presented in one graph.

We will take a look at Obama’s first inauguration speech from 2009 and Trumps recent speech. We will analyse the sentiments of the speeches and compare them.

Monte Carlo simulation is a stochastic method, in which a large number of random experiments is performed. This is helpful, especially if there is no analytical solution to a problem. I will present “Buffon’s needle” problem. The idea is to throw a needle on a grid with horizontal lines. The probability of a needle intersecting …

Monte Carlo Simulation, explained based on Buffons Needle Problem Read More »

We will perform a Market Basket Analysis (also called Association Rules). This techniques shows which items occur together, like “users who bought X, also bought Y and Z”. We will use this method to find out, which properties are important to conclude that a mushroom is edible.

Introduction In this tutorial we will take a look at measurements of Hubble (the telescope). Besides taking beautiful pictures, it measured speed and distance of Super-Novae. Similar data was used in 1929 by Hubble (the person) and he found out that there is a linear relationship. We will create a linear model based on observations …

Training a simple linear model Read More »

H2O is an open source platform for machine learning. It can be installed locally. It offers API access to R. This lecture will give you an introduction on how to use it. Objectives: Installation and Usage of H2O Requirements: R Data-Mining

In this tutorial we will take a look at deep learning with neuralnet package – a package with which you can create neural networks. Objectives: deep learning with neuralnet package; create a model for mushroom classification Requirements: R Basics

In this tutorial you will learn what the bias-variance tradeoff is and how this problem can be solved with cross validation.

We will create a Random Forest and a Support Vector Machine model for income prediction. We will also learn what a Receiver Operating Characteristic (ROC) is and how to interpret it. Objectives: Model Creation, Random Forest, SVM, Prediction, ROC-Curve Requirements: R Basics, R Data Mining