Learning Libraries

878 Components & Libraries

Sortby

Learning Libraries

DIPY is the paragon 3D/4D+ imaging library in Python. Contains generic methods for spatial normalization, signal processing, machine learning, statistical analysis and visualization of medical images. Additionally, it contains specialized methods for computational anatomy including diffusion, perfusion and structural imaging.

You can find our sources and single-click downloads: DIPY can be installed using pip: or using conda:

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Moreover, there are parsers for file formats common in NLP (e.g. FoLiA/Giza/Moses/ARPA/Timbl/CQL). There are also clients to interface with various NLP specific servers. PyNLPl most notably features a very extensive library for working with FoLiA XML (Format for Linguistic Annotation).

PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks s…

scikit-learn: machine learning in Python

It is currently maintained by a team of volunteers. scikit-learn requires: You can check the latest sources with the command: The project is currently maintained by a team of volunteers.

Machine learning for NeuroImaging in Python

Nilearn enables approachable and versatile analyses of brain volumes. It provides statistical and machine-learning tools, with instructive documentation & friendly community. Execute the followin…

Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Pattern is a web mining module for Python. It has tools for: It is well documented, thoroughly tested with 350+ unit tests and comes bundled with 50+ examples. The source code is licensed under BSD. …

Medical image processing in Python

MedPy is an image processing library and collection of scripts targeted towards medical (i.e. high dimensional) image processing.

A platform for end-to-end development of machine learning solutions in biomedical imaging

In the era of Deep Learning, developing robust machine learning solutions to problems in biomedical imaging requires access to large amounts of annotated training data, objective comparisons of state…

A tutorial for Kaggle's Titanic: Machine Learning from Disaster competition. Demonstrates basic data munging, analysis, and visualization techniques. Shows examples of supervised machine learning techniques.

This is a tutorial in an IPython Notebook for the Kaggle competition, Titanic Machine Learning From Disaster. The goal of this repository is to provide an example of a competitive analysis for those …

The official repository for ROOT: analyzing, storing and visualizing big data, scientifically

The ROOT system provides a set of modules with all the functionality needed to handle and analyze large amounts of data in a very efficient way. Having the data defined as a set of objects, specializ…

SciKit-Learn Laboratory (SKLL) makes it easy to run machine learning experiments.

This Python package provides command-line utilities to make it easier to run machine learning experiments with scikit-learn. One of the primary goals of our project is to make it so that you can run…

Tutorials about Quantitative Finance in Python and QuantLib: Pricing, xVAs, Hedging, Portfolio Optimisation, Machine Learning and Deep Learning

Here you find my IPython (Jupyter) notebooks from my blog (ipythonquant.wordpress.org). Feel free to download the samples and play around with them.

Metric learning algorithms in Python

If you use metric-learn in a scientific publication, we would appreciate citations to the following paper: Bibtex entry:

A toolkit for making real world machine learning and data analysis applications in C++

Go into the examples folder and type: That will build all the examples. If you have a CPU that supports AVX instructions then turn them on like this: Doing so will make some things run faster. Finall…

Machine Learning Benchmark Scripts

Develop branch build status: This repository contains a collection of benchmark scripts for various machine learning libraries. The scripts serve as an infrastructure for measuring and comparing the …

A python client for connecting to all the services provided by https://dandelion.eu

pyclustering is a Python, C++ data mining library.

Installation using pip3 tool: Manual installation from official repository using Makefile: Manual installation using CMake: Manual installation using Microsoft Visual Studio solution: If you are usin…

H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

GitHub GitHub issues -- file bug reports / track issues here Stack Overflow -- ask all code/software questions here Cross Validated (Stack Exchange) -- ask algorithm/theory questions here h2ostream G…

A framework for high-performance medical image processing, neural network inference and visualization

FAST is an open-source framework with the main goal of making it easier to do high-performance processing, neural network inference, and visualization of medical images utilizing multi-core CPUs and …

Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

Sacred is a tool to help you configure, organize, log and reproduce experiments. It is designed to do all the tedious overhead work that you need to do around your actual experiment in order to: Sacr…

Some small utility modules to help with pandas, numpy and sklearn usage in other projects

PicNet and Predict Bench provide predictive analytics services and products like Centazio. These products and services are supported by this library that combines best in breed libraries, implementa…

Tika-Python is a Python binding to the Apache Tika™ REST services allowing Tika to be called natively in the Python community.

This makes Apache Tika available as a Python library, installable via Setuptools, Pip and Easy Install. To use this library, you need to have Java 7+ installed on your system as tika-python starts up…

A collection of machine learning examples and tutorials.

A collection of machine learning examples and tutorials. Please note that not all code from all courses will be found in this repository. Some newer code examples (e.g. most of Tensorflow 2.0) were d…

MapReduce, Spark, Java, and Scala for Data Algorithms Book

The book's codebase can also be downloaded from the git repository at: Thank you!

A library of extension and helper modules for Python's data analysis and machine learning libraries.

Sebastian Raschka 2014-2024 To install mlxtend, just execute If you use conda, to install mlxtend just execute The mlxtend version on PyPI may always be one step behind; you can install the latest de…

A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

imbalanced-learn requires the following dependencies: Additionally, imbalanced-learn requires the following optional dependencies: The examples will requires the following additional dependencies: im…

practical introduction to Python for machine learning, with pandas and scikit-learn - Sept 2014

We will be reviewing the materials with Jupyter notebooks. You should be able to type in your terminal window and see the notebook panel load in your web browser.

:newspaper: Let ChatGPT Summarize Hacker News for You

Emoji explained: Translation is also performed by ChatGPT, with a single extra step in the prompt. Currently supported languages:

Python toolkit for pluggable algorithms and data structures for multimedia-based machine learning.

As of Jan 2021, SMQTK v0.14.0 has been deprecated. The various interfaces and implementations have been broken out into the following distinct packages which will continue to be supported instead. So…

Related tags