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  2. 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 ...

  3. 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).

  4. Comparison of deep learning software - Wikipedia

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

    The following tables compare notable software frameworks, libraries, and computer programs for deep ... List of datasets for machine-learning research; List of ...

  5. List of statistical software - Wikipedia

    en.wikipedia.org/wiki/List_of_statistical_software

    OpenNN – A software library written in the programming language C++ which implements neural networks, a main area of deep learning research; Orange, a data mining, machine learning, and bioinformatics software; Pandas – High-performance computing (HPC) data structures and data analysis tools for Python in Python and Cython (statsmodels ...

  6. Machine learning - Wikipedia

    en.wikipedia.org/wiki/Machine_learning

    The computational analysis of machine learning algorithms and their performance is a branch of theoretical computer science known as computational learning theory via the probably approximately correct learning model. Because training sets are finite and the future is uncertain, learning theory usually does not yield guarantees of the ...

  7. ML.NET - Wikipedia

    en.wikipedia.org/wiki/ML.NET

    ML.NET is a free software machine learning library for the C# and F# programming languages. [4] [5] [6] It also supports Python models when used together with NimbusML.The preview release of ML.NET included transforms for feature engineering like n-gram creation, and learners to handle binary classification, multi-class classification, and regression tasks. [7]

  8. Statistical learning theory - Wikipedia

    en.wikipedia.org/wiki/Statistical_learning_theory

    Statistical learning theory is a framework for machine learning drawing from the fields of statistics and functional analysis. [ 1 ] [ 2 ] [ 3 ] Statistical learning theory deals with the statistical inference problem of finding a predictive function based on data.

  9. Torch (machine learning) - Wikipedia

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

    Torch is an open-source machine learning library, a scientific computing framework, and a scripting language based on Lua. [3] It provides LuaJIT interfaces to deep learning algorithms implemented in C. It was created by the Idiap Research Institute at EPFL. Torch development moved in 2017 to PyTorch, a port of the library to Python. [4] [5] [6]