See RnnRNN and general weights, gradients, & activations visualization in Keras & TensorFlow
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Multilstmkeras attentional bi-LSTM-CRF for Joint NLU (slot-filling and intent detection) with ATIS
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Text predictorChar-level RNN LSTM text generator📄.
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DeeplearningfornlpinpytorchAn IPython Notebook tutorial on deep learning for natural language processing, including structure prediction.
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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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Deep Learning With PythonExample projects I completed to understand Deep Learning techniques with Tensorflow. Please note that I do no longer maintain this repository.
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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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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
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Chinese Chatbot中文聊天机器人,基于10万组对白训练而成,采用注意力机制,对一般问题都会生成一个有意义的答复。已上传模型,可直接运行,跑不起来直播吃键盘。
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JlmA fast LSTM Language Model for large vocabulary language like Japanese and Chinese
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Deep GenerationI used in this project a reccurent neural network to generate c code based on a dataset of c files from the linux repository.
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ContextConText v4: Neural networks for text categorization
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A RecsysA Tensorflow based implicit recommender system
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EasyocrReady-to-use OCR with 80+ supported languages and all popular writing scripts including Latin, Chinese, Arabic, Devanagari, Cyrillic and etc.
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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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Nlp Models TensorflowGathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0
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StockpredictionPlain Stock Close-Price Prediction via Graves LSTM RNNs
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E3d lstme3d-lstm; Eidetic 3D LSTM A Model for Video Prediction and Beyond
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ExermoteUsing Machine Learning to predict the type of exercise from movement data
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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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Numpy MlMachine learning, in numpy
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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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Awesome Deep Learning ResourcesRough list of my favorite deep learning resources, useful for revisiting topics or for reference. I have got through all of the content listed there, carefully. - Guillaume Chevalier
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Pytorch convlstmconvolutional lstm implementation in pytorch
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Repo 2016R, Python and Mathematica Codes in Machine Learning, Deep Learning, Artificial Intelligence, NLP and Geolocation
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Image Caption Generator[DEPRECATED] A Neural Network based generative model for captioning images using Tensorflow
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Stock Market Prediction Web App Using Machine Learning And Sentiment AnalysisStock Market Prediction Web App based on Machine Learning and Sentiment Analysis of Tweets (API keys included in code). The front end of the Web App is based on Flask and Wordpress. The App forecasts stock prices of the next seven days for any given stock under NASDAQ or NSE as input by the user. Predictions are made using three algorithms: ARIMA, LSTM, Linear Regression. The Web App combines the predicted prices of the next seven days with the sentiment analysis of tweets to give recommendation whether the price is going to rise or fall
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Daguan 2019 rank9datagrand 2019 information extraction competition rank9
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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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SarcasmdetectionSarcasm detection on tweets using neural network
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EthnicolrPredict Race and Ethnicity Based on the Sequence of Characters in a Name
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Reinforcementlearning AtarigamePytorch LSTM RNN for reinforcement learning to play Atari games from OpenAI Universe. We also use Google Deep Mind's Asynchronous Advantage Actor-Critic (A3C) Algorithm. This is much superior and efficient than DQN and obsoletes it. Can play on many games
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Multitask sentiment analysisMultitask Deep Learning for Sentiment Analysis using Character-Level Language Model, Bi-LSTMs for POS Tag, Chunking and Unsupervised Dependency Parsing. Inspired by this great article https://arxiv.org/abs/1611.01587
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Handwriting SynthesisImplementation of "Generating Sequences With Recurrent Neural Networks" https://arxiv.org/abs/1308.0850
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Lstm AutoencodersAnomaly detection for streaming data using autoencoders
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Deep Learning ResourcesA Collection of resources I have found useful on my journey finding my way through the world of Deep Learning.
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Document Classifier LstmA bidirectional LSTM with attention for multiclass/multilabel text classification.
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Lstm CrfA (CNN+)RNN(LSTM/BiLSTM)+CRF model for sequence labelling.😏
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Rnn Text Classification TfTensorflow Implementation of Recurrent Neural Network (Vanilla, LSTM, GRU) for Text Classification
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