/courses/machine-learning/unsupervised-learning/Recent content in Unsupervised Learning on DATATWEETSHugoenCopyright (c) 2025 DatatweetsFri, 14 Nov 2025 09:00:00 +0200/courses/machine-learning/unsupervised-learning/lesson-1-introduction-to-unsupervised-learning/Fri, 14 Nov 2025 09:00:00 +0200/courses/machine-learning/unsupervised-learning/lesson-1-introduction-to-unsupervised-learning/Discover what unsupervised learning is, how it differs from supervised learning, and why clustering is its headline task. You will meet the real Mall Customers dataset and learn to spot natural groups by eye before any algorithm runs./courses/machine-learning/unsupervised-learning/lesson-2-the-iterative-k-means-algorithm/Fri, 14 Nov 2025 09:00:00 +0200/courses/machine-learning/unsupervised-learning/lesson-2-the-iterative-k-means-algorithm/Open up the k-means algorithm and see exactly how it discovers clusters. You will pick k, initialize centroids, and repeat the assign-and-update loop on the real Mall Customers dataset until the centroids stop moving, while learning the inertia objective, why standardization matters, and how smart initialization with k-means++ helps./courses/machine-learning/unsupervised-learning/lesson-3-choosing-the-number-of-clusters-with-the-elbow-method/Fri, 14 Nov 2025 09:00:00 +0200/courses/machine-learning/unsupervised-learning/lesson-3-choosing-the-number-of-clusters-with-the-elbow-method/Answer the central question of k-means: how many clusters? You will measure inertia, plot the elbow curve, and use the silhouette score as a complementary metric on the real Mall Customers dataset, then see why both point to five clusters./courses/machine-learning/unsupervised-learning/lesson-4-k-means-with-scikit-learn-and-interpreting-results/Fri, 14 Nov 2025 09:00:00 +0200/courses/machine-learning/unsupervised-learning/lesson-4-k-means-with-scikit-learn-and-interpreting-results/Use scikit-learn’s KMeans to segment mall customers from start to finish: scale the data, fit the model, read labels_ and cluster_centers_, then profile and name each of the five segments. You will turn raw cluster numbers into an actionable marketing story./courses/machine-learning/unsupervised-learning/lesson-5-guided-project-wholesale-customer-segmentation/Fri, 14 Nov 2025 09:00:00 +0200/courses/machine-learning/unsupervised-learning/lesson-5-guided-project-wholesale-customer-segmentation/Bring everything together in a guided clustering project. You will load the real Wholesale Customers dataset, log-transform skewed spending, standardize it, use the elbow method to pick k, fit KMeans, visualize high-dimensional clusters with PCA, and profile each segment into a business story.