gpt-gmm-tsne-pre.py

import matplotlib.pyplot as plt
import matplotlib

matrix = clean_data['ada_embedding'].to_list()

# Create a t-SNE model and transform the data
tsne = TSNE(n_components=2, perplexity=15, random_state=42, init='random', learning_rate=200)
vis_dims = tsne.fit_transform(matrix)

x = [x for x,y in vis_dims]
y = [y for x,y in vis_dims]

plt.figure(figsize=(20,10))
plt.scatter(x, y, alpha=0.3)