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1 Deep learning software by name. 2 Comparison of machine learning model compatibility. 3 See also. ... Download as PDF; Printable version; In other projects Wikidata ...
TensorFlow is a software library for machine learning and artificial intelligence. It can be used across a range of tasks, but is used mainly for training and inference of neural networks . [ 3 ] [ 4 ] It is one of the most popular deep learning frameworks, alongside others such as PyTorch and PaddlePaddle.
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The plain transformer architecture had difficulty converging. In the original paper [1] the authors recommended using learning rate warmup. That is, the learning rate should linearly scale up from 0 to maximal value for the first part of the training (usually recommended to be 2% of the total number of training steps), before decaying again.
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Direct members of this category should be general-purpose software for training or otherwise interacting with deep learning models. Specific deep learning models, or consumer software applications powered by deep learning, should be placed in Category:Deep learning software applications.
It implements deep architectures with multiple non-linear layers and contains utilities to solve function regression, pattern recognition, time series and autoencoding problems. [ citation needed ] The input to Neural Designer is a data set, and its output is a predictive model .
Torch is an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua. [3] It provides LuaJIT interfaces to deep learning algorithms implemented in C. It was created by the Idiap Research Institute at EPFL. Torch development moved in 2017 to PyTorch, a port of the library to Python. [4] [5] [6]