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2. TensorFlow - Wikipedia

   en.wikipedia.org/wiki/TensorFlow

   TensorFlow can be used in a wide variety of programming languages, including Python, JavaScript, C++, and Java, [12] facilitating its use in a range of applications in many sectors. History [ edit ]

3. Keras - Wikipedia

   en.wikipedia.org/wiki/Keras

   Keras is an open-source library that provides a Python interface for artificial neural networks. Keras was first independent software, then integrated into the TensorFlow library, and later supporting more. "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers ...

4. 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

5. Python (programming language) - Wikipedia

   en.wikipedia.org/wiki/Python_(programming_language)

   Python is a high-level, general-purpose programming language. Its design philosophy emphasizes code readability with the use of significant indentation. [33] Python is dynamically type-checked and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented and functional ...

6. Neural network software - Wikipedia

   en.wikipedia.org/wiki/Neural_network_software

   Basic types of neural networks are simple to implement directly. There are also many programming libraries that contain neural network functionality and that can be used in custom implementations (such as TensorFlow, Theano, etc., typically providing bindings to languages such as Python, C++, Java).

7. CuPy - Wikipedia

   en.wikipedia.org/wiki/CuPy

   CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.

8. 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 ...

9. Tensor (machine learning) - Wikipedia

   en.wikipedia.org/wiki/Tensor_(machine_learning)

   In machine learning, the term tensor informally refers to two different concepts (i) a way of organizing data and (ii) a multilinear (tensor) transformation. Data may be organized in a multidimensional array (M-way array), informally referred to as a "data tensor"; however, in the strict mathematical sense, a tensor is a multilinear mapping over a set of domain vector spaces to a range vector ...