Kelvin Lin

import numpy as np from PIL import Image as im import matplotlib.pyplot as plt import sklearn.datasets as datasets # Create a synthetic dataset centers = [[0, 0], [3, 3], [-4, 3], [3, -4]] X, _ = datasets.make_blobs(n_samples=300, centers=centers, cluster_std=0.9, random_state=0) class DBSCAN: def __init__(self, data, eps, min_samples): """Initialize DBSCAN with data, epsilon radius, and min_samples.""" self.data = data self.eps = eps self.min_samples = min_samples self.labels = np.array([-1]...

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Back when I was a clueless college freshman, I had no idea what an API was. I thought it sounded fancy — like something you needed a secret clearance to understand. And then there was this thing called a RESTful API, which somehow sounded even more intimidating. But everyone kept throwing those words around like they were common sense, and I knew if I didn’t figure it out fast, I’d be left in the dust.