NLP, Llm, Deep Learning, Machine Learning, Mathematics.
[model.wv[word] for word in labels] tsne_model = TSNE(perplexity=40, n_components=2, init='pca', n_iter=2500, random_state=23) new_values = tsne_model.fit_transform(vectors) x, y = [], [] for value in new_values: x.append(value[0]) y.append(value[1]) plt.figure(figsize=(10, 8)) for i in