chore: import upstream snapshot with attribution

examples/t-sne.py

@@ -0,0 +1,28 @@
+import logging
+
+import matplotlib.pyplot as plt
+from sklearn.datasets import make_classification
+
+from mla.tsne import TSNE
+
+logging.basicConfig(level=logging.DEBUG)
+
+X, y = make_classification(
+    n_samples=500,
+    n_features=10,
+    n_informative=5,
+    n_redundant=0,
+    random_state=1111,
+    n_classes=2,
+    class_sep=2.5,
+)
+
+p = TSNE(2, max_iter=500)
+X = p.fit_transform(X)
+
+colors = ["red", "green"]
+for t in range(2):
+    t_mask = (y == t).astype(bool)
+    plt.scatter(X[t_mask, 0], X[t_mask, 1], color=colors[t])
+
+plt.show()