Deep learning frameworks serve as the implementation backbone for neural network concepts. Some frameworks are primarily designed for both training and inference tasks—such as TensorFlow, PyTorch, and FastAI. Others are specifically optimized for high-speed inference in real-world applications, including OpenVino and TensorRT.
