K Means Clustering Algorithm in Machine Learning
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the_iitian_coder on Instagram: "Data finds its own groups with K-Means 📊 Learn Machine Learning step-by-step with The IITIAN Coder 🚀 K-Means is an unsupervised machine learning algorithm used to group similar data points together. First, we decide how many groups (K) we want. The algorithm randomly selects K center points called centroids, then assigns each data point to the nearest centroid. After that, the centroids are updated by taking the average of the points in each group. This process
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AI • Machine Learning • Tech on Instagram: "One of the most common ML interview questions is how to implement k-means clustering from scratch. What is k-means? Simply put, it’s an unsupervised clustering algorithm that groups data into k clusters, where k is a hyperparameter we select. The algorithm has the following steps: Initialize k centroids, Assign each data point to the nearest centroid, Update centroids to the mean of the assigned points, Repeat until convergence. Want to Learn Machine L
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