PyTorch
What it is: Meta's ML framework. Pythonic, dynamic graphs, research-friendly. Most popular for deep learning research.
What It Does Best
Research and experimentation. Dynamic computation graphs. Build models that change based on input. Debug with Python debugger.
Pythonic API. Feels like NumPy. Easy to learn if you know Python.
Strong community. Most new research papers use PyTorch. Cutting-edge implementations available.
Pricing
Free. Open source, BSD license.
When to Use It
✅ Research and prototyping
✅ Learning deep learning
✅ Custom model architectures
✅ Following latest research papers
When NOT to Use It
❌ Need production serving out of box (TensorFlow Serving better)
❌ Mobile deployment primary goal
❌ Classical ML only (scikit-learn simpler)
Bottom line: Won the hearts of researchers. More intuitive than TensorFlow. If you're learning or researching, start here. Production deployment is maturing fast.