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  2. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    Keras allows users to produce deep models on smartphones (iOS and Android), on the web, or on the Java Virtual Machine. [8] It also allows use of distributed training of deep-learning models on clusters of graphics processing units (GPU) and tensor processing units (TPU) .

  3. 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 ...

  4. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    Google JAX is a machine learning framework for transforming numerical functions. [ 71 ] [ 72 ] [ 73 ] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and TensorFlow's XLA (Accelerated Linear Algebra).

  5. JAX (software) - Wikipedia

    en.wikipedia.org/wiki/JAX_(software)

    JAX is a Python library that provides a machine learning framework for transforming numerical functions developed by Google with some contributions from Nvidia. [2] [3] [4] It is described as bringing together a modified version of autograd (automatic obtaining of the gradient function through differentiation of a function) and OpenXLA's XLA (Accelerated Linear Algebra).

  6. Chainer - Wikipedia

    en.wikipedia.org/wiki/Chainer

    Chainer was the first deep learning framework to introduce the define-by-run approach. [10] [11] The traditional procedure to train a network was in two phases: define the fixed connections between mathematical operations (such as matrix multiplication and nonlinear activations) in the network, and then run the actual training calculation. This ...

  7. Probably approximately correct learning - Wikipedia

    en.wikipedia.org/wiki/Probably_approximately...

    Foundations of Machine Learning. MIT Press, 2018. Chapter 2 contains a detailed treatment of PAC-learnability. Readable through open access from the publisher. D. Haussler. Overview of the Probably Approximately Correct (PAC) Learning Framework. An introduction to the topic. L. Valiant. Probably Approximately Correct. Basic Books, 2013.

  8. PyTorch - Wikipedia

    en.wikipedia.org/wiki/PyTorch

    Although the Python interface is more polished and the primary focus of development, PyTorch also has a C++ interface. [ 14 ] A number of pieces of deep learning software are built on top of PyTorch, including Tesla Autopilot , [ 15 ] Uber 's Pyro, [ 16 ] Hugging Face 's Transformers, [ 17 ] [ 18 ] and Catalyst.

  9. scikit-learn - Wikipedia

    en.wikipedia.org/wiki/Scikit-learn

    scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language. [3] It features various classification, regression and clustering algorithms including support-vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific ...