Some weeks ago I had a presentation at my work place about “R for data science” that I’d like to share with you. I’ve written the slides in R and rmarkdown and uploaded them to rpubs.com. I chose to use rmarkdown for my slides although we have great company PowerPoint templates, because I wanted to … Continue reading Presentation “R for Data Science”

# Tag: data analysis

## Data Analysis with Microsoft Excel: Tables

Auf ambassadorbase.at ist mein Artikel auf Deutsch verfügbar. In my job and my studies I recently finished I work with lots of different data sources and you will also meet all of them throughout your career as a data scientist. Data can be given to you as an SQL dump, XML files and many other … Continue reading Data Analysis with Microsoft Excel: Tables

## Finding data sets Part 2: TV, music, book ratings and sports data

The first part gave a more general overview on where to get data. This section will give you specific data sources, e.g. if you like sports, movies, books, … and so on. Over the next couple of weeks you’ll find these posts on my blog: General data sources TV, music, book ratings and sports data … Continue reading Finding data sets Part 2: TV, music, book ratings and sports data

## Finding data sets Part 1: General data sources

I often encounter interesting algorithms or R packages which I want to test. The nice ones provide data for testing but often it is only dummy data. To get a good understanding of the method and its limitations real data might be required. Sometimes I would also like to explore data I have not used … Continue reading Finding data sets Part 1: General data sources

## [Dimensionality Reduction #2] Understanding Factor Analysis using R

This time I am going to show you how to perform Factor analysis. In the next post I will show you some scaling and projection methods. The idea for this mini-series was inspired by a Machine Learning (Unsupervised) lecture I had at university. I will perform all this methods on the same data sets and … Continue reading [Dimensionality Reduction #2] Understanding Factor Analysis using R

## [Dimensionality Reduction #1] Understanding PCA and ICA using R

This time I am going to show you how to perform PCA and ICA. In the next one or two posts I will show you Factor Analysis and some scaling and projection methods. The idea for this mini-series was inspired by a Machine Learning (Unsupervised) lecture I had at university. I will perform all this … Continue reading [Dimensionality Reduction #1] Understanding PCA and ICA using R