tiny-rnnLightweight C++11 library for building deep recurrent neural networks
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Multi Class Text Classification Cnn RnnClassify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.
Stars: ✭ 570 (+251.85%)
hcnHybrid Code Networks https://arxiv.org/abs/1702.03274
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Rnn For Joint NluPytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling" (https://arxiv.org/abs/1609.01454)
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Lstm peptidesLong short-term memory recurrent neural networks for learning peptide and protein sequences to later design new, similar examples.
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HasteHaste: a fast, simple, and open RNN library
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Chameleon recsysSource code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems
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Speech-RecognitionEnd-to-end Automatic Speech Recognition for Madarian and English in Tensorflow
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See RnnRNN and general weights, gradients, & activations visualization in Keras & TensorFlow
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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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Har Stacked Residual Bidir LstmsUsing deep stacked residual bidirectional LSTM cells (RNN) with TensorFlow, we do Human Activity Recognition (HAR). Classifying the type of movement amongst 6 categories or 18 categories on 2 different datasets.
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Pytorch Seq2seqTutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
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lstm harLSTM based human activity recognition using smart phone sensor dataset
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KprnReasoning Over Knowledge Graph Paths for Recommendation
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EBIM-NLIEnhanced BiLSTM Inference Model for Natural Language Inference
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Pytorch Image Comp RnnPyTorch implementation of Full Resolution Image Compression with Recurrent Neural Networks
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tf-ran-cellRecurrent Additive Networks for Tensorflow
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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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air writingOnline Hand Writing Recognition using BLSTM
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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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Dense BiLSTMTensorflow Implementation of Densely Connected Bidirectional LSTM with Applications to Sentence Classification
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myDLDeep Learning
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ConvLSTM-PyTorchConvLSTM/ConvGRU (Encoder-Decoder) with PyTorch on Moving-MNIST
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Word Rnn TensorflowMulti-layer Recurrent Neural Networks (LSTM, RNN) for word-level language models in Python using TensorFlow.
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ThesemicolonThis repository contains Ipython notebooks and datasets for the data analytics youtube tutorials on The Semicolon.
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Char rnn lm zhlanguage model in Chinese,基于Pytorch官方文档实现
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Hred Attention TensorflowAn extension on the Hierachical Recurrent Encoder-Decoder for Generative Context-Aware Query Suggestion, our implementation is in Tensorflow and uses an attention mechanism.
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Document Classifier LstmA bidirectional LSTM with attention for multiclass/multilabel text classification.
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Awd Lstm LmLSTM and QRNN Language Model Toolkit for PyTorch
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QrnQuery-Reduction Networks (QRN)
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Nspm🤖 Neural SPARQL Machines for Knowledge Graph Question Answering.
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RnnoiseRecurrent neural network for audio noise reduction
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VpilotScripts and tools to easily communicate with DeepGTAV. In the future a self-driving agent will be implemented.
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NcrfppNCRF++, a Neural Sequence Labeling Toolkit. Easy use to any sequence labeling tasks (e.g. NER, POS, Segmentation). It includes character LSTM/CNN, word LSTM/CNN and softmax/CRF components.
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Mnist ClassificationPytorch、Scikit-learn实现多种分类方法,包括逻辑回归(Logistic Regression)、多层感知机(MLP)、支持向量机(SVM)、K近邻(KNN)、CNN、RNN,极简代码适合新手小白入门,附英文实验报告(ACM模板)
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ExermoteUsing Machine Learning to predict the type of exercise from movement data
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DeeplearningfornlpinpytorchAn IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.
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TesseractThis package contains an OCR engine - libtesseract and a command line program - tesseract.
Tesseract 4 adds a new neural net (LSTM) based OCR engine which is focused
on line recognition, but also still supports the legacy Tesseract OCR engine of
Tesseract 3 which works by recognizing character patterns. Compatibility with
Tesseract 3 is enabled by using the Legacy OCR Engine mode (--oem 0).
It also needs traineddata files which support the legacy engine, for example
those from the tessdata repository.
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