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  2. François Chollet - Wikipedia

    en.wikipedia.org/wiki/François_Chollet

    Chollet is the author of Xception: Deep Learning with Depthwise Separable Convolutions, [10] which is among the top ten most cited papers in CVPR proceedings at more than 18,000 citations. [11] Chollet is the author of the book Deep Learning with Python, [12] which sold over 100,000 copies, and the co-author with Joseph J. Allaire of Deep ...

  3. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    [4] Designed to enable fast experimentation with deep neural networks, Keras focuses on being user-friendly, modular, and extensible. It was developed as part of the research effort of project ONEIROS (Open-ended Neuro-Electronic Intelligent Robot Operating System), [5] and its primary author and maintainer is François Chollet, a Google engineer.

  4. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    Python: Python: Only on Linux No Yes No Yes Yes Keras: François Chollet 2015 MIT license: Yes Linux, macOS, Windows: Python: Python, R: Only if using Theano as backend Can use Theano, Tensorflow or PlaidML as backends Yes No Yes Yes [20] Yes Yes No [21] Yes [22] Yes MATLAB + Deep Learning Toolbox (formally Neural Network Toolbox) MathWorks ...

  5. Deep learning - Wikipedia

    en.wikipedia.org/wiki/Deep_learning

    Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.

  6. Fine-tuning (deep learning) - Wikipedia

    en.wikipedia.org/wiki/Fine-tuning_(deep_learning)

    In deep learning, fine-tuning is an approach to transfer learning in which the parameters of a pre-trained neural network model are trained on new data. [1] Fine-tuning can be done on the entire neural network, or on only a subset of its layers, in which case the layers that are not being fine-tuned are "frozen" (i.e., not changed during backpropagation). [2]

  7. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    [3] [4] It is one of the most popular deep learning frameworks, alongside others such as PyTorch and PaddlePaddle. [ 5 ] [ 6 ] It is free and open-source software released under the Apache License 2.0 .

  8. Automated machine learning - Wikipedia

    en.wikipedia.org/wiki/Automated_machine_learning

    Automated machine learning can target various stages of the machine learning process. [3] Steps to automate are: Data preparation and ingestion (from raw data and miscellaneous formats) Column type detection; e.g., Boolean, discrete numerical, continuous numerical, or text

  9. Multilayer perceptron - Wikipedia

    en.wikipedia.org/wiki/Multilayer_perceptron

    In deep learning, a multilayer perceptron (MLP) is a name for a modern feedforward neural network consisting of fully connected neurons with nonlinear activation functions, organized in layers, notable for being able to distinguish data that is not linearly separable.

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