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  2. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    Numpy is one of the most popular Python data libraries, and TensorFlow offers integration and compatibility with its data structures. [66] Numpy NDarrays, the library's native datatype, are automatically converted to TensorFlow Tensors in TF operations; the same is also true vice versa. [ 66 ]

  3. Google JAX - Wikipedia

    en.wikipedia.org/wiki/Google_JAX

    It is designed to follow the structure and workflow of NumPy as closely as possible and works with various existing frameworks such as TensorFlow and PyTorch. [5] [6] The primary functions of JAX are: [2] grad: automatic differentiation; jit: compilation; vmap: auto-vectorization; pmap: Single program, multiple data (SPMD) programming

  4. Convolutional neural network - Wikipedia

    en.wikipedia.org/wiki/Convolutional_neural_network

    TensorFlow: Apache 2.0-licensed Theano-like library with support for CPU, GPU, Google's proprietary tensor processing unit (TPU), [160] and mobile devices. Theano: The reference deep-learning library for Python with an API largely compatible with the popular NumPy library. Allows user to write symbolic mathematical expressions, then ...

  5. Recurrent neural network - Wikipedia

    en.wikipedia.org/wiki/Recurrent_neural_network

    TensorFlow: Apache 2.0-licensed Theano-like library with support for CPU, GPU and Google's proprietary TPU, [116] mobile; Theano: A deep-learning library for Python with an API largely compatible with the NumPy library. Torch: A scientific computing framework with support for machine learning algorithms, written in C and Lua.

  6. NumPy - Wikipedia

    en.wikipedia.org/wiki/NumPy

    NumPy (pronounced / ˈ n ʌ m p aɪ / NUM-py) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. [3]

  7. Open-source artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Open-source_artificial...

    Open-source artificial intelligence has brought widespread accessibility to machine learning (ML) tools, enabling developers to implement and experiment with ML models across various industries. Sci-kit Learn, Tensorflow, and PyTorch are three of the most widely used open-source ML libraries, each contributing unique capabilities to the field. [58]

  8. Tensor Processing Unit - Wikipedia

    en.wikipedia.org/wiki/Tensor_Processing_Unit

    Tensor Processing Unit (TPU) is an AI accelerator application-specific integrated circuit (ASIC) developed by Google for neural network machine learning, using Google's own TensorFlow software. [2] Google began using TPUs internally in 2015, and in 2018 made them available for third-party use, both as part of its cloud infrastructure and by ...

  9. 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.