Deep neural networks topic
Deep neural networks (DNNs) are a class of artificial neural networks (ANNs) that are deep in the sense that they have many layers of hidden units between the input and output layers. Deep neural networks are a type of deep learning, which is a type of machine learning. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing. Deep neural networks are used in a variety of applications, including speech recognition, computer vision, and natural language processing.
GermanWordEmbeddings
Toolkit to obtain and preprocess German text corpora, train models and evaluate them with generated testsets. Built with Gensim and Tensorflow.
APPNP
A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).
FEATHER
The reference implementation of FEATHER from the CIKM '20 paper "Characteristic Functions on Graphs: Birds of a Feather, from Statistical Descriptors to Parametric Models".
pytorch-examples
Tutorials, examples, and projects implemented with PyTorch
gluon2pytorch
Gluon to PyTorch deep neural network model converter
deep-sudoku-solver
A Sudoku Solver that leverages TensorFlow and iOS BNNS for deep learning.
deep-learning-roadmap
my own deep learning mastery roadmap
deeplearning4recommendersystem
deep learning for recommender system
bruno
a deep recurrent model for exchangeable data
deep-atrous-cnn-sentiment
Deep-Atrous-CNN-Text-Network: End-to-end word level model for sentiment analysis and other text classifications