Before I give you an answer to this question let’s take a step back and first have a look at what we mean by dimensional data modelling.
Yesterday, I talked about Machine Learning, and the huge impact it will have in the world in the future. Today, I’d like to talk about a similar paradigm, that often gets mixed up with it, but that is not the same thing at all. I’m talking about Deep learning.
Machine learning has been a hot topic. But what is machine learning?
On this set of exercises, we are going to use the lm and glm functions to perform several generalized linear models on one dataset. Since this is a basic set of exercises we will take a closer look at the arguments of these functions and how to take advantage of the output of each function so we can find a model that fits our data. Before starting this set of exercises, I strongly suggest you look at the R Documentation of lm and glm. Note: This set of exercises assume that you have a basic understanding of generalized linear models.
Creating a meaningful visualization from data with long lists can be challenging. While word clouds are often the popular choice, they are not always the best option. This post illustrates seven alternatives to word clouds that can be used to visualize data from long lists, each has its own trade-offs. The visualization examples in this post use the GDP of 185 countries and are created using R.