PyTorch

PyTorch's dynamic computation graphs make it intuitive for experimentation and debugging. Its Pythonic design and eager execution model align with how researchers think about and prototype new ideas.

Yes, PyTorch has matured significantly for production use with TorchServe, TorchScript for optimization, and ONNX export. Companies like Meta, Tesla, and Microsoft use PyTorch in production systems.

PyTorch Lightning is a high-level framework that organizes PyTorch code and eliminates boilerplate. It handles training loops, distributed training, and logging while keeping your research code clean.

Start with the official PyTorch tutorials and the 'Learn PyTorch for Deep Learning' course. Focus on tensors, autograd, building neural networks, and training loops before moving to advanced topics.