Factor analysis is a statistical technique used to reduce the number of dimensions in order to simplify additional analysis or confirm a construct. In this video, we will look at a very simple example of factor analysis along with a visualization.

Natural language processing is a tool used in data science to modify texts in order to extract meaning. The video below will go through some basics of this processing. For an added bonus, there is also an example of making a word cloud.

Random forest is a machine learning algorithm that makes multiple decision trees in order to make the best decision. By making many trees you can avoid the mistake of overfitting to the data, which is a common weakness of decision trees.

Decision trees are common tool used in data science and machine learning. In the video below we will learn how to develop a simple decision tree using Python.

Principal component analysis is a tool for reducing the number of variables in a dataset without losing too much information. This is a great way to summarize information or to simplify things for a more complex analysis. The video provides a simple example of how to do this.

Python has a great library called that Altair that makes it really easy to make various data visualizations. The primary strength of this particular library is how easy it is to use and to also create interactive plots. The video below provides an introduction to using this innovative tool.

We are going to take a look at Altair which is a data visulization library for Python. What is unique abiut Altair compared to other packages experienced on this blog is that it allows for interactions. The interactions can take place inside jupyter or they can be exported and loaded ...

Random forest is a type of machine learning algorithm in which the algorithm makes multiple decision trees that may use different features and subsample to making as many trees as you specify. The trees then vote to determine the class of an example. This approach helps to deal with the ...