Hey! Welcome to the wild world of ML in Python. For how to run machine learning python scripts without the chaos, I’d say start with Jupyter notebooks for experimenting—they’re great for debugging step by step.
But for bigger projects, .py files + terminal are cleaner. Also, dependency errors? Ugh, the worst. Always use virtual envs (venv or conda) to avoid library conflicts.
Pro tip: `pip freeze > requirements.txt` saves your setup so others (or future you) can replicate it.
But for bigger projects, .py files + terminal are cleaner. Also, dependency errors? Ugh, the worst. Always use virtual envs (venv or conda) to avoid library conflicts.
Pro tip: `pip freeze > requirements.txt` saves your setup so others (or future you) can replicate it.