.. blogpost::
    :title: Quelques modules intéressants
    :keywords: pyFFTW, fftw3, DTW, kNN, Flt-SNE
    :date: 2018-11-30
    :categories: modules

    * `pyFFTW <https://github.com/pyFFTW/pyFFTW>`_
      (`fftw3 <https://github.com/FFTW/fftw3>`_)
    * `K Nearest Neighbors & Dynamic Time Warping <https://github.com/markdregan/K-Nearest-Neighbors-with-Dynamic-Time-Warping>`_
    * `FFT-accelerated Interpolation-based t-SNE (FIt-SNE) <https://github.com/KlugerLab/FIt-SNE>`_
    * `py-spy <https://github.com/benfred/py-spy>`_
    * `kalman-filter <https://github.com/hbcbh1999/kalman-filter>`_

    Depuis le site `Awesome Functional Python <https://github.com/hbcbh1999/awesome-functional-python>`_ :

    * `PyFunctional <https://github.com/EntilZha/PyFunctional>`_
      (ressemble pas mal à
      `Linq <https://docs.microsoft.com/fr-fr/dotnet/csharp/programming-guide/concepts/linq/introduction-to-linq-queries>`_)
    * `hask <https://github.com/billpmurphy/hask>`_
      (inspiré de `Haskell <https://www.haskell.org/>`_)
    * `pyramda <https://github.com/jackfirth/pyramda>`_

    Quelques cours :

    * `Machine Learning Yarning <https://github.com/hbcbh1999/ml-yearning>`_
    * `Foundations of Machine Learning <https://bloomberg.github.io/foml/#lectures>`_
      (`github <https://github.com/hbcbh1999/mlcourse>`_)