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  2. PyDev - Wikipedia

    en.wikipedia.org/wiki/PyDev

    PyDev received improvements to type inference and a notable increase in contributions to code base when version 2.8 was released in July 2013. [6] Since then, numerous additional improvements have been made to PyDev and it has gained many positive reviews. [7] [8] Version 5.4.0 was released on November 30, 2016.

  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. Matplotlib - Wikipedia

    en.wikipedia.org/wiki/Matplotlib

    Matplotlib (portmanteau of MATLAB, plot, and library [3]) is a plotting library for the Python programming language and its numerical mathematics extension NumPy.It provides an object-oriented API for embedding plots into applications using general-purpose GUI toolkits like Tkinter, wxPython, Qt, or GTK.

  5. It teaches fundamental principles of computer programming, including recursion, abstraction, modularity, and programming language design and implementation. MIT Press published the first edition in 1984, and the second edition in 1996. It was formerly used as the textbook for MIT's introductory course in computer science.

  6. Spyder (software) - Wikipedia

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

    It is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language.Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software.

  7. Compilers: Principles, Techniques, and Tools - Wikipedia

    en.wikipedia.org/wiki/Compilers:_Principles...

    Compilers: Principles, Techniques, and Tools [1] is a computer science textbook by Alfred V. Aho, Monica S. Lam, Ravi Sethi, and Jeffrey D. Ullman about compiler construction for programming languages. First published in 1986, it is widely regarded as the classic definitive compiler technology text.

  8. File:Python Programming eBook Reader.pdf - Wikipedia

    en.wikipedia.org/wiki/File:Python_Programming...

    You are free: to share – to copy, distribute and transmit the work; to remix – to adapt the work; Under the following conditions: attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made.

  9. Bootstrapping (compilers) - Wikipedia

    en.wikipedia.org/wiki/Bootstrapping_(compilers)

    Bootstrapping a compiler has the following advantages: [6] It is a non-trivial test of the language being compiled, and as such is a form of dogfooding.; Compiler developers and bug reporters only need to know the language being compiled.