Hello, Data and AI enthusiasts!
K-means clustering is one of the most popular unsupervised learning algorithms, a class of machine learning algorithms that can be used to find patterns in unlabeled data. Clustering algorithms work by classifying data into similar groups or clusters and labeling them so that they can be used for supervised learning. IBM watsonx.ai is an enterprise studio offering for AI builders that integrates all parts of the AI and Data Science lifecycle into one Hybrid Cloud platform for developers. In this month's newsletter, you'll find articles that explain the fundamentals of performing K-means clustering in Python or R by using IBM Watson Studio Jupyter Notebooks on watsonx.ai.