Pytorch Sentiment AnalysisTutorials on getting started with PyTorch and TorchText for sentiment analysis.
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RnnsharpRNNSharp is a toolkit of deep recurrent neural network which is widely used for many different kinds of tasks, such as sequence labeling, sequence-to-sequence and so on. It's written by C# language and based on .NET framework 4.6 or above versions. RNNSharp supports many different types of networks, such as forward and bi-directional network, sequence-to-sequence network, and different types of layers, such as LSTM, Softmax, sampled Softmax and others.
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Lstm Human Activity RecognitionHuman Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier
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SpeakerDiarization RNN CNN LSTMSpeaker Diarization is the problem of separating speakers in an audio. There could be any number of speakers and final result should state when speaker starts and ends. In this project, we analyze given audio file with 2 channels and 2 speakers (on separate channels).
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sequence-rnn-pySequence analyzing using Recurrent Neural Networks (RNN) based on Keras
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DeepseqslamThe Official Deep Learning Framework for Route-based Place Recognition
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tiny-rnnLightweight C++11 library for building deep recurrent neural networks
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Pytorch Kaldipytorch-kaldi is a project for developing state-of-the-art DNN/RNN hybrid speech recognition systems. The DNN part is managed by pytorch, while feature extraction, label computation, and decoding are performed with the kaldi toolkit.
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Rnn ctcRecurrent Neural Network and Long Short Term Memory (LSTM) with Connectionist Temporal Classification implemented in Theano. Includes a Toy training example.
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Linear Attention Recurrent Neural NetworkA recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)
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Pytorch Pos TaggingA tutorial on how to implement models for part-of-speech tagging using PyTorch and TorchText.
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Document Classifier LstmA bidirectional LSTM with attention for multiclass/multilabel text classification.
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Image Caption Generator[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow
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Stock Price PredictorThis project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.
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Keras LmuKeras implementation of Legendre Memory Units
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CS231nMy solutions for Assignments of CS231n: Convolutional Neural Networks for Visual Recognition
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Sequence-Models-courseraSequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.
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IseebetteriSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
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danifojo-2018-repeatrnnComparing Fixed and Adaptive Computation Time for Recurrent Neural Networks
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lstm harLSTM based human activity recognition using smart phone sensor dataset
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ACTAlternative approach for Adaptive Computation Time in TensorFlow
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dltfHands-on in-person workshop for Deep Learning with TensorFlow
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tf-ran-cellRecurrent Additive Networks for Tensorflow
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StockpredictionPlain Stock Close-Price Prediction via Graves LSTM RNNs
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Image Caption GeneratorA neural network to generate captions for an image using CNN and RNN with BEAM Search.
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Deep News SummarizationNews summarization using sequence to sequence model with attention in TensorFlow.
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Pytorch-POS-TaggerPart-of-Speech Tagger and custom implementations of LSTM, GRU and Vanilla RNN
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Rnn From ScratchUse tensorflow's tf.scan to build vanilla, GRU and LSTM RNNs
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Dense BiLSTMTensorflow Implementation of Densely Connected Bidirectional LSTM with Applications to Sentence Classification
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totally humansrnn trained on r/totallynotrobots 🤖
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rnn2dCPU and GPU implementations of some 2D RNN layers
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Human-Activity-RecognitionHuman activity recognition using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six categories (WALKING, WALKING_UPSTAIRS, WALKING_DOWNSTAIRS, SITTING, STANDING, LAYING).
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DrowsyDriverDetectionThis is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy.
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VariationalNeuralAnnealingA variational implementation of classical and quantum annealing using recurrent neural networks for the purpose of solving optimization problems.
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datastories-semeval2017-task6Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".
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ArrayLSTMGPU/CPU (CUDA) Implementation of "Recurrent Memory Array Structures", Simple RNN, LSTM, Array LSTM..
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air writingOnline Hand Writing Recognition using BLSTM
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EBIM-NLIEnhanced BiLSTM Inference Model for Natural Language Inference
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novel writerTrain LSTM to writer novel (HongLouMeng here) in Pytorch.
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deep-improvisationEasy-to-use Deep LSTM Neural Network to generate song sounds like containing improvisation.
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dtsA Keras library for multi-step time-series forecasting.
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Speech-RecognitionEnd-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
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question-pairA siamese LSTM to detect sentence/question pairs.
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theano-recurrenceRecurrent Neural Networks (RNN, GRU, LSTM) and their Bidirectional versions (BiRNN, BiGRU, BiLSTM) for word & character level language modelling in Theano
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ConvLSTM-PyTorchConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST
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CS231nPyTorch/Tensorflow solutions for Stanford's CS231n: "CNNs for Visual Recognition"
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