A logistic regression is a model that is appropriate to use when the dependent variable is binary, i.e. 0s and 1s, True or False, Yes or No. The logistic regression is part of the regression analysis library and could therefor be interpreted as a predictive analytics model.
The purpose of a pie chart is to tell a story about the parts-to-whole aspect of your data. In other words, it describes how big one part is compared to other parts. This all sounds like a visualization with a good purpose, so why shouldn’t you use it?
K-Means clustering is one of the most popular unsupervised machine learning algorithms. It is a classification algorithm, meaning it’s purpose is to arrange the unlabeled data by shared qualities and characteristics.
There are hundreds of Python libraries aimed to make lives easier for data scientists. Some good and some bad, some large libraries covering many areas and some that only do a couple things very well. Here is a list of 5 Python libraries that every data scientist is required to have installed in their environment.
In this blog post I will lay out five (5) reasons you should consider Databricks before starting your next data science project.
Both correlation and causation are statistical terms that are often misunderstood. Understanding both of these concepts is vital before making a decision based on data.
There are a lot of blogs out there focusing on data science. Throughout the past few years, I have found at least a handful of blogs that I read regularly. I’ve tried my best to narrow it down to my favorite 5 blogs.
Welcome to the home of Classy Data! Here we are going to examine the world of data science while looking at interesting findings and walking through machine learning examples. In addition to machine learning and AI, we are also going to be looking at other tools that are used in the data science and analytics space, such as dashboard visualization and cloud computing. First of all, I’d like to introduce myself. My name is Stian Ulriksen. I am located in Denver, CO at the foothills of the Rocky Mountains. Currently I am working as a Data Scientist Consultant for a consulting company where we help clients with everything from migrating to the cloud, all the way to deep learning data science projects. As I am a big fan of Python, this blog will mostly focus on examples written in Python (sorry you R lovers out there). If that sounds good…