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Illustration of transfer learning. Transfer learning ( TL) is a technique in machine learning (ML) in which knowledge learned from a task is re-used in order to boost performance on a related task. [1] For example, for image classification, knowledge gained while learning to recognize cars could be applied when trying to recognize trucks.
A transformer is a deep learning architecture developed by Google and based on the multi-head attention mechanism, proposed in a 2017 paper "Attention Is All You Need". [1] Text is converted to numerical representations called tokens, and each token is converted into a vector via looking up from a word embedding table. [1]
Keras. Keras is an open-source library that provides a Python interface for artificial neural networks. Keras was first independent software, then integrated into TensorFlow library, and later supporting more. "Keras 3 is a full rewrite of Keras [can be used] as a low-level cross-framework language to develop custom components such as layers ...
TensorFlow serves as a core platform and library for machine learning. TensorFlow's APIs use Keras to allow users to make their own machine-learning models. [41] In addition to building and training their model, TensorFlow can also help load the data to train the model, and deploy it using TensorFlow Serving.
Zero-shot learning. Zero-shot learning ( ZSL) is a problem setup in deep learning where, at test time, a learner observes samples from classes which were not observed during training, and needs to predict the class that they belong to. The name is a play on words based on the earlier concept of one-shot learning, in which classification can be ...
Text-to-Text Transfer Transformer (T5) T5 (Text-to-Text Transfer Transformer) is a series of large language models developed by Google AI. Introduced in 2019, [1] T5 models are trained on a massive dataset of text and code using a text-to-text framework. The T5 models are capable of performing the text-based tasks that they were pretrained for.
Knowledge distillation. In machine learning, knowledge distillation or model distillation is the process of transferring knowledge from a large model to a smaller one. While large models (such as very deep neural networks or ensembles of many models) have higher knowledge capacity than small models, this capacity might not be fully utilized.
François Chollet ( French: [fʁɑ̃swa ʃoˈlɛ]; born 20 October 1989) is a French software engineer and artificial intelligence researcher currently working at Google. Chollet is the creator of the Keras deep-learning library, released in 2015. His research focuses on computer vision, the application of machine learning to formal reasoning ...