Displaying 1 to 17 from 17 results

mlcourse_open - OpenDataScience Machine Learning course. Both in English and Russian

  •    Python

This is the list of published articles on medium.com 🇬🇧, habr.com 🇷🇺, and jqr.com 🇨🇳. Icons are clickable. Also, links to Kaggle Kernels (in English) are given. This way one can reproduce everything without installing a single package. Assignments will be announced each week. Meanwhile, you can pratice with demo versions. Solutions will be discussed in the upcoming run of the course.

librosa - Python library for audio and music analysis

  •    Python

A python package for music and audio analysis. See http://librosa.github.io/librosa/ for a complete reference manual and introductory tutorials.




madmom - Python audio and music signal processing library

  •    Python

Madmom is an audio signal processing library written in Python with a strong focus on music information retrieval (MIR) tasks. The library is internally used by the Department of Computational Perception, Johannes Kepler University, Linz, Austria (http://www.cp.jku.at) and the Austrian Research Institute for Artificial Intelligence (OFAI), Vienna, Austria (http://www.ofai.at).

docker-alpine-python-machinelearning - Small Docker image with Python Machine Learning tools (~180MB) https://hub

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Small Docker image with Python Machine Learning tools (~180MB) https://hub.docker.com/r/frolvlad/alpine-python-machinelearning/

pytorch-notebook - Jupyter Notebook Pytorch Stack

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This image is based on Jupyter Notebook Scientific Python Stack. The following command starts a container with the Notebook server listening for HTTP connections on port 8888 with a randomly generated authentication token configured.


stft - Spectrogram calculation for NumPy

  •    Python

This is a package for calculating the short time fourier transform (spectrogram) or any other transform in a lapped and windowed fashion. Loading a file and calculating the spectrogram, its inverse and saving the result.

Scipy-Bordeaux-2017 - Course taught at the University of Bordeaux in the academic year 2017 for PhD students

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Lecture notes from the course taught at the University of Bordeaux in the academic year 2017 for PhD students. Each student needs to come with a notebook computer running either Linux, OSX or Windows. The scientific Python ecosystem is made of several modules that constitute together the scientific stack. There are hundreds of Python scientific packages and most of them are built on top of numpy, scipy, matplotib, pandas, cython and/or sympy. We won't cover everything in this short course, but you should get enough information to decide if your research can benefit from Python. And I bet it will likely do.

instakit - Image processors and filters for use with ImageKit

  •    Python

Instakit† is a suite of image processors and filters, for processing PIL images. InstaKit processors use the same API as PILKit's, so they can be used with anything that supports those, including ImageKit. Or you can just use them by themselves to process images using Python.

SciFortran - A library of fortran modules and routines for scientific calculations (*in a way* just like scipy for python)

  •    Fortran

This is a unitary collection of fortran modules and procedures for scientific calculations. The library aims to provide a simple and generic environment for any scientific or mathematic computations. The project is largely inspired by SciPy for Python and tries to closely follow its guidelines and naming convention. There are large areas that are still not covered. Anyone is welcome to contribute or to test the software.

hetmech - Matrix-based storage & computation on hetnets to enable a search engine for hetnets

  •    Jupyter

Hetmech aims to identify the relevant network connections between a set of query nodes. The method is designed to operate on hetnets (networks with multiple node or relationship types). This project is still under development. Use with caution.

numpycpp - A c++ header library for matrix operation inspired Numpy Scipy, MATLAB only using Eigen.

  •    C++

A c++ header library for matrix operation inspired Numpy, Scipy and MATLAB only using Eigen. This library has some APIs which Numpy, Scipy, MATLAB has, but Eigen doesn't.

spampy - Spam filtering module with Machine Learning using SVM (Support Vector Machines).

  •    Python

Spam filtering module with Machine Learning using SVM. spampy is a classifier that uses Support Vector Machines which tries to classify given raw emails if they are spam or not. Support vector machines (SVMs) are supervised learning models with associated learning algorithms that analyze data used for classification and regression analysis. Given a set of training examples, each marked as belonging to one or the other of two categories, an SVM training algorithm builds a model that assigns new examples to one category or the other, making it a non-probabilistic binary linear classifier.