ML frameworks
| # | File | Covers |
|---|---|---|
| 01 | What is PyTorch? | PyTorch fundamentals |
| 02 | What is TensorFlow? | TensorFlow fundamentals |
| 03 | PyTorch vs TensorFlow | the comparison |
| 04 | PyTorch — Common Interview Questions and Answers | PyTorch questions |
| 05 | TensorFlow — Common Interview Questions and Answers | TensorFlow questions |
| 06 | Choosing an ML framework | the 2026 map — scikit-learn, gradient boosting, JAX, Optuna |
The practical answer: scikit-learn is still the default for classical modelling and clean pipelines, gradient boosting still dominates structured data, and PyTorch is the default for deep learning because it’s what research and the entire LLM ecosystem target. You rarely choose — you use what your pretrained checkpoint was published in.