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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. Anaconda (Python distribution) - Wikipedia

   en.wikipedia.org/wiki/Anaconda_(Python_distribution)

   Anaconda is a distribution of the Python and R programming languages for scientific computing (data science, machine learning applications, large-scale data processing, predictive analytics, etc.), that aims to simplify package management and deployment. The distribution includes data-science packages suitable for Windows, Linux, and macOS.

4. Comparison of deep learning software - Wikipedia

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

   Retrieved 2022-09-27. ^ a b Atilim Gunes Baydin; Barak A. Pearlmutter; Alexey Andreyevich Radul; Jeffrey Mark Siskind (20 February 2015). "Automatic differentiation in machine learning: a survey". arXiv: 1502.05767 [cs.LG]. ^ "Microsoft/caffe". GitHub. 30 October 2021. ^ "Caffe: a fast open framework for deep learning".

5. 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 ...

6. TensorFlow - Wikipedia

   en.wikipedia.org/wiki/TensorFlow

   v. t. e. TensorFlow is a free and open-source software library for machine learning and artificial intelligence. It can be used across a range of tasks but has a particular focus on training and inference of deep neural networks. [3][4] It is one of the two most popular deep learning libraries alongside PyTorch.

7. PyTorch - Wikipedia

   en.wikipedia.org/wiki/PyTorch

   PyTorch is a machine learning library based on the Torch library, [4] [5] [6] used for applications such as computer vision and natural language processing, [7] originally developed by Meta AI and now part of the Linux Foundation umbrella.

8. 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]

9. pandas (software) - Wikipedia

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

   Website. pandas.pydata.org. Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis. In particular, it offers data structures and operations for manipulating numerical tables and time series. It is free software released under the three-clause BSD license. [2]