Machine learning is one of the most influential and rapidly growing fields in all of computer technology. If you’re interested in getting into machine learning, you’ll need to familiarize yourself with the basic concepts relevant to the field, like algorithms, variables, and different types of model analysis. While there is much more to learn than what is covered in this article, this brief crash course in machine learning will provide you with some definitions/intuitions regarding…

The confusion matrix is one of the most powerful tools for predictive analysis in machine learning. A confusion matrix gives you information about how your machine classifier has performed, pitting properly classified examples against misclassified examples. Let’s take a look at how to interpret a confusion matrix and how a confusion matrix can be implemented in Scikit-learn for Python. What Is a Confusion Matrix? Perhaps you are wondering: What exactly is a “confusion matrix”? Put…

Logistic regression is one of the most common and useful classification algorithms in machine learning. If you wish to become a better machine learning practitioner, you’ll definitely want to familiarize yourself with logistic regression. Let’s take some time to understand how logistical regression functions and situations where it should be utilized. Defining Machine Learning Terms Logistic regression is a type of classification algorithm. Yet what does “classification” mean? As a machine learning practitioner, you’ll need…