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
- IA y aprendizaje automático, Bioinformática, Visión por computadora, Análisis de datos, Procesamiento de señales
- Inteligencia Artificial (IA), Aprendizaje profundo, Aprendizaje automático, Red neuronal, Tecnología de redes neuronales, Fuente abierta, Creación de prototipos, Software
Características:
- 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)
Precios:
- Gratis
- 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.
Ideal para:
- Researchers and developers in machine learning and artificial intelligence, particularly for deep learning model development, experimentation, and deployment.