10 Must-Know Machine Learning Algorithms for Data Scientists
Machine learning is the science of getting computers to act without being explicitly programmed.” — Andrew Ng
Machine learning algorithms are a crucial part of data science, allowing us to make predictions and understand complex data sets. In this guide, we will cover the top 10 machine learning algorithms that every data scientist should know.
1. K-Nearest Neighbors (KNN)
KNN is a simple but powerful classification algorithm that uses data point proximity to determine class membership. It works by identifying the K data points that are closest to the data point in question, and then assigning the data point to the class that is most represented among those K points.
Key features of KNN include:
- Easy to implement and understand
- Can be used for both classification and regression
- Flexible, as the number of nearest neighbors (K) can be adjusted
A real-world example of KNN in action is in credit scoring, where it can be used to predict the likelihood of a loan applicant defaulting on their loan.
