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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.
Parse tree generated with NLTK. The Natural Language Toolkit, or more commonly NLTK, is a suite of libraries and programs for symbolic and statistical natural language processing (NLP) for English written in the Python programming language.
O'Reilly Media, Inc. (formerly O'Reilly & Associates) is an American learning company established by Tim O'Reilly that provides technical and professional skills development courses via an online learning platform. O'Reilly also publishes books about programming and other technical content.
David Beazley is an American software engineer. He has made significant contributions to the Python developer community, which includes writing the definitive Python reference text Python Essential Reference, the SWIG software tool for creating language agnostic C and C++ extensions, and the PLY parsing tool.
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 ...
JAX is a machine learning framework for transforming numerical functions. [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).
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
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).
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