The Unreasonable Effectiveness of Transfer Learning
Last Updated on August 18, 2023 by Editorial Team
Author(s): Satyam Kumar
Originally published on Towards AI.
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Training a complex deep-learning neural network requires significant computational efficiency, the availability of a large corpus of data, and better feature learning architecture to achieve state-of-the-art results. But these requirements are only sometimes satisfied for start-ups, researchers, and students. With the recent advancement of deep learning, many pre-trained models are now open-sourced.
Some of the popular convolution neural network-based pre-trained models are VGG16/19, ResNet, MobileNet, EfficientNet, ResNeXt, and many more. The weights and the architecture of these pre-trained models can be tuned to use them… Read the full blog for free on Medium.
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