An open-source machine learning framework that accelerates the path from research prototyping to production deployment, known for its flexibility and Pythonic nature.
PyTorch

- Python
- KI und maschinelles Lernen, Bioinformatik, Computer Vision, Datenanalyse, Signalverarbeitung
- Künstliche Intelligenz (KI), Tiefes Lernen, Maschinelles Lernen, Neurales Netzwerk, Neuronale Netzwerktechnologie, Open Source, Prototyping, Software
Merkmale:
- Tensor computation (similar to NumPy) with strong GPU acceleration,automatic differentiation for building and training neural networks (autograd),dynamic computation graphs,deep neural network modules and layers,optimizers (SGD,Adam,etc.),distributed training support,Python-first approach,ecosystem of tools and libraries (TorchVision,TorchText,TorchAudio)
Preisgestaltung:
- Kostenlos
- Highly flexible and Python-friendly, dynamic computation graphs are great for research and complex models (especially NLP), strong GPU support, large and active research community, good for rapid prototyping and deployment.
- Can have a steeper learning curve than Keras for beginners, debugging can sometimes be tricky, production deployment tools are maturing but historically were less straightforward than TensorFlow's in some aspects.
Am besten geeignet für:
- Researchers and developers in machine learning and artificial intelligence, particularly for deep learning model development, experimentation, and deployment.