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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide: A practical guide to building neural networks using Microsoft's open source deep learning framework. Packt Publishing. ISBN 978-1789802993
A large collection of Question to SPARQL specially design for Open Domain Neural Question Answering over DBpedia Knowledgebase. This dataset contains a large collection of Open Neural SPARQL Templates and instances for training Neural SPARQL Machines; it was pre-processed by semi-automatic annotation tools as well as by three SPARQL experts.
The codebase for AlexNet was released under a BSD license, and had been commonly used in neural network research for several subsequent years. [ 20 ] [ 17 ] In one direction, subsequent works aimed to train increasingly deep CNNs that achieve increasingly higher performance on ImageNet.
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a model inspired by the structure and function of biological neural networks in animal brains. [1] [2] An ANN consists of connected units or nodes called artificial neurons, which loosely model the neurons in the brain. Artificial ...
NNI (Neural Network Intelligence) is a free and open-source AutoML toolkit developed by Microsoft. [3] [4] It is used to automate feature engineering, model compression, neural architecture search, and hyper-parameter tuning. [5] [6] The source code is licensed under MIT License and available on GitHub. [7]
NeuroSolutions is a neural network development environment developed by NeuroDimension.It combines a modular, icon-based (component-based) network design interface with an implementation of advanced learning procedures, such as conjugate gradients, the Levenberg-Marquardt algorithm, and back-propagation through time.
The International Conference on Learning Representations (ICLR) is a machine learning conference typically held in late April or early May each year. Along with NeurIPS and ICML, it is one of the three primary conferences of high impact in machine learning and artificial intelligence research.
A neural network is a group of interconnected units called neurons that send signals to one another. Neurons can be either biological cells or mathematical models. While individual neurons are simple, many of them together in a network can perform complex tasks. There are two main types of neural network.