Feedback on t-SNE script: ideas to improve clarity and usability

Feature description

Hi! I tested your t_stochastic_neighbour_embedding.py script on my local setup and it runs well thanks for sharing it!

I have a few suggestions that might improve clarity and usability for others:

Visualization: Consider adding a matplotlib scatter plot to show the t-SNE result. It helps users see the clustering visually.

Reproducibility: Adding random_state=42 to the TSNE() constructor would make the output consistent across runs.

Parameter transparency: Explicitly setting perplexity, learning_rate, and n_iter could help learners understand how t-SNE behaves.

Import error handling: A simple try/except block for sklearn imports could guide users if they haven't installed the package.

Let me know if you'd like help implementing any of these — happy to collaborate!

Comienza leyendo t_stochastic_neighbour_embedding.py y el uso actual de TSNE. Revisa los cambios propuestos en materia de visualización, reproducibilidad, parámetros y gestión de imports; después, confirma qué sugerencias están dentro del alcance. Se considera terminado cuando las mejoras seleccionadas están implementadas y el script sigue ejecutándose como se espera.