Branch of Machine Learning dealing with Unsupervised Learning.
In machine learning, there are two types: those who like to keep things short and sweet and those who want to explain everything in detail. I fall into the latter category – I love verbosity. Some might call it overkill,…
Even though clustering is a cornerstone of data science and data mining, many falsely assume that clustering does not come without its challenges. In this 9-minute read, we will go over the challenges of clustering, what clustering is, the different…
In data science, some underlying assumptions are made when you use specific machine learning models. Many of these assumptions are based on the distributions of your data. With this 5-minute read, we will explore how to find the current distributions…
While K means clustering is one of the most famous clustering algorithms, what happens when you are clustering categorical variables or dealing with binary data? K means clustering depends on the data points being continuous, where an average (mean) is…
Evaluating a clustering algorithm is much different than evaluating a classification or regression machine learning algorithm. In a classification problem, labels will be given for the data points, giving you a reference point to create your accuracy measure. What happens…
Topic modeling is a dense but gratifying subject. Knowing how to put your text into specific topics is crucial to understanding the different genres within your text. Utilizing topic modeling also allows you to quickly ingest ideas from your text…
