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2. Python (programming language) - Wikipedia

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

   Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [36] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [37] [38] [39] [40]

3. 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 ...

4. Natural Language Toolkit - Wikipedia

   en.wikipedia.org/wiki/Natural_Language_Toolkit

   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. It supports classification, tokenization, stemming, tagging, parsing, and semantic reasoning functionalities. [4]

5. RUR-PLE - Wikipedia

   en.wikipedia.org/wiki/RUR-PLE

   RUR - Python Learning Environment (RUR-PLE) is an educational tool to help students learn the Python programming language. Made by André Roberge. RUR-PLE uses the idea behind Karel the Robot, making the learning of Python programming more interesting. A student writes a program that controls a 'robot' that moves through a city consisting of a ...

6. 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. Anaconda distribution includes data-science packages suitable for Windows, Linux, and macOS ...

7. General-purpose programming language - Wikipedia

   en.wikipedia.org/wiki/General-purpose...

   [14] [15] The former allowed non-software engineers to easily learn and write computer programs, while the latter allowed domain specialists to easily create libraries suited to their own use cases. For these reasons, Python has been used across a wide range of domains. Below are some of the areas where Python is used: [16]