K-means clustering is an unsupervised machine learning algorithm used to partition data points into k distinct clusters, where each data point belongs to the cluster with the nearest mean (centroid). It is commonly used for data segmentation, anomaly detection, and image compression.
Whether you're looking to get your foot in the door, find the right person to talk to, or close the deal — accurate, detailed, trustworthy, and timely information about the organization you're selling to is invaluable.
Use Sumble to: