Published on Sep 28, 2022
There are three widely used frameworks for deep learning research and production today. As a result, one of them is lauded for its ease of use, another for its features and maturity, and a third for its immense scalability. How should you choose between the two?
There are many ways in which deep learning is changing our lives every day, both in small and large ways. There seems to be a new technological advance every month, whether it is Siri or Alexa answering our voice commands, the real-time translation apps on our phones, or the computer vision technology that helps smart tractors, warehouse robots, and self-driving cars to operate. It is important to note that nearly all of these deep learning applications are written in one of three frameworks: TensorFlow, PyTorch, and JAX.
