awesome-advanced-metering-infrastructure

A machine learning / bayesian inference assigning attributes to objects.

А fast and framework agnostic image augmentation library that implements a diverse set of augmentation techniques. Supports classification, segmentation, detection out of the box. Was used to win a number of Deep Learning competitions at Kaggle, Topcoder and those that were a part of the CVPR workshops.

Materials and IPython notebooks for "Smart Building and meter Analysis" by LaGuer.

Approximate nearest neighbours implementation.

An Apache Incubating project for developing an open source machine learning library.

Support Vector Machines, Decision Trees, Naive Bayesian models, K-means, Gaussian Mixture models and general algorithms such as Ransac, Cross-validation and Grid-Search for machine-learning applications. This package is part of the Accord.NET Framework.

Together with AForge.NET, this library can provide image processing and computer vision algorithms to Windows, Windows RT and Windows Phone. Some components are also available for Java and Android.

Open source C# framework for developers and researchers in the fields of Computer Vision and Artificial Intelligence. Development has now shifted to GitHub.

An automatic differentiation (AD) library providing exact and efficient derivatives (gradients, Hessians, Jacobians, directional derivatives, and matrix-free Hessian- and Jacobian-vector products) for machine learning and optimization applications. Operations can be nested to any level, meaning that you can compute exact higher-order derivatives and differentiate functions that are internally making use of differentiation, for applications such as hyperparameter optimization.

Cross platform wrapper of OpenCV which can be compiled in Mono to be run on Windows, Linus, Mac OS X, iOS, and Android.

A machine learning library by Airbnb designed from the ground up to be human friendly.

A Java Toolbox for Scalable Probabilistic Machine Learning.

Apache clinical Text Analysis and Knowledge Extraction System (cTAKES) is an open-source natural language processing system for information extraction from electronic medical record clinical free-text.

The ClearNLP project provides software and resources for natural language processing. The project started at the Center for Computational Language and EducAtion Research, and is currently developed by the Center for Language and Information Research at Emory University. This project is under the Apache 2 license.

ClearTK provides a framework for developing statistical natural language processing (NLP) components in Java and is built on top of Apache UIMA.

Platform for data visualization and analysis, using the

Julia artificial neural networks.

Basic functions for clustering data: k-means, dp-means, etc.

Julia package for Regularized Discriminant Analysis.

Data structures that allow missing values.

library for working with tabular data in Julia.

Metaprogramming tools for DataFrames.

Scripts to generate a dataset with static frames from the Arcade Learning Environment.

Autograd automatically differentiates native Torch code. Inspired by the original Python version.

Cephes mathematical functions library, wrapped for Torch. Provides and wraps the 180+ special mathematical functions from the Cephes mathematical library, developed by Stephen L. Moshier. It is used, among many other places, at the heart of SciPy.

Torch CUDA Neural Network Implementation.

Torch CUDA Implementation.