What are the most popular frameworks for neural networks?
By zilliz
1 min read
Popular frameworks for neural networks include TensorFlow, PyTorch, and Keras. TensorFlow, developed by Google, is widely used for large-scale production and research. PyTorch, preferred in academic circles, offers a flexible and dynamic computation graph.
Keras, built on TensorFlow, provides a high-level API for rapid prototyping. Other frameworks like MXNet, CNTK, and JAX cater to specific needs like distributed training or gradient-based optimization.
The choice of framework depends on factors like ease of use, community support, and compatibility with existing tools. Many developers opt for frameworks with extensive libraries and pre-trained models.