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Deep learning frameworks are used to create deep and machine learning models. They provide tried-and-true foundations for building and training deep neural networks, and offer concise methods for defining models that make use of already developed and optimised functions. The top 10 deep learning frameworks for 2023 are TensorFlow, Keras, PyTorch, MxNet, and Caffe. These frameworks provide practical and evidence-based methods for developing machine or deep learning algorithms, which speeds up the process and yields results that are significantly more accurate than if the model were built from scratch.
