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Search results for lstm word embeddings
lstm
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word-embeddings
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30 search results found
Pytorch Sentiment Analysis
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4,133
Tutorials on getting started with PyTorch and TorchText for sentiment analysis.
Multi Class Text Classification Cnn Rnn
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554
Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.
Personality Detection
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273
Implementation of a hierarchical CNN based model to detect Big Five personality traits
Named Entity Recognition With Bidirectional Lstm Cnns
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241
Named-Entity-Recognition-with-Bidirectional-LSTM-C
Hands On Deep Learning Algorithms With Python
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241
Master Deep Learning Algorithms with Extensive Math by Implementing them using TensorFlow
Chameleon_recsys
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202
Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems
Relation Classification Using Bidirectional Lstm Tree
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183
TensorFlow Implementation of the paper "End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures" and "Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths" for classifying relations
Datastories Semeval2017 Task4
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171
Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis".
Mimick
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149
Code for Mimicking Word Embeddings using Subword RNNs (EMNLP 2017)
Pytorch Rnn Text Classification
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145
Word Embedding + LSTM + FC
Nlp De Cero A Cien
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135
Curso práctico: NLP de cero a cien 🤗
Yelp_comments_classification_nlp
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61
Yelp round-10 review comments classification using deep learning (LSTM and CNN) and natural language processing.
Lstm Context Embeddings
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56
Augmenting word embeddings with their surrounding context using bidirectional RNN
Pytorch Crf
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41
🔥 A PyTorch implementation of a Bi-LSTM CRF with character-level features
Sequence Models Coursera
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34
Sequence Models by Andrew Ng on Coursera. Programming Assignments and Quiz Solutions.
Text Analysis
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32
Explaining textual analysis tools in Python. Including Preprocessing, Skip Gram (word2vec), and Topic Modelling.
Contextuallstm
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26
Contextual LSTM for NLP tasks like word prediction and word embedding creation for Deep Learning
Deepspamreview Detection Of Fake Reviews On Online Review Platforms Using Deeplearning Architectures
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25
DeepSpamReview: Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures. Summer Internship project at CoreView Systems.
Retrieval Based_chatbot
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24
Sentimentanalysis
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22
Sentiment Analysis: Deep Bi-LSTM+attention model
Deepsentipers
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22
Repository for the experiments described in the paper named "DeepSentiPers: Novel Deep Learning Models Trained Over Proposed Augmented Persian Sentiment Corpus"
Datastories Semeval2017 Task6
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19
Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".
Pos Tagging Bilstm Crf
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16
A Tensorflow 2, Keras implementation of POS tagging using Bidirectional LSTM-CRF on Penn Treebank corpus (WSJ)
Hands On Nlp With Pytorch
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15
Collection of Notebooks for Natural Language Processing with PyTorch
Grammatical Error Detection
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12
Etymon
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9
Find the origin of words in every language using a Deep Neural Network trained to create an etymological map.
Emosense Semeval2019 Task3 Emocontext
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9
Deep-learning system presented in "EmoSence at SemEval-2019 Task 3: Bidirectional LSTM Network for Contextual Emotion Detection in Textual Conversations" at SemEval-2019.
Densely Connected Bidirectional Lstm
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7
这是一个denseNet_bilstm
Romanian Diacritic Restoration
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7
Automatically restore Romanian diacritics from flat text using neural nets
Readingcomprehension
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7
Bi-Directional Attention Flow for Machine Comprehensions
Analysing Imdb Reviews Using Glove And Lstm
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6
Using the IMDB data found in Keras here a few algorithms built with Keras. The source code is from Francois Chollet's book Deep learning with Python. The aim is to predict whether a review is positive or negative just by analyzing the text. Both self-created as well as pre-trained (GloVe) word embeddings are used. Finally there's a LSTM model and the accuracies of the different algorithms are compared. For the LSTM model I had to cut the data sets of 25.000 sequences by 80% to 5.000, since my l
Keras Applications
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6
Keras 응용(CNN, RNN, GAN, DNN, ETC...) 사용법 예시
Smash
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6
This project aims to create new tweets and carry out social engineering attacks by using the messages that people sent from social media accounts. Deep learning methods are used in this project. Besides, the model is trained with the social media messages of the people and new messages are created with this model. Malicious links are designed for people's interests. The study was implemented as a project developed only in the graduate course of ethical hacking. It is for educational purposes.
Chatbot
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6
a naive chatbot that sometimes misdiagnoses
Auth Id
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5
A hierarchical bi-LSTM model trained to identify the author of a given email (SMAI@IIIT-H 2017)
Image_captioning
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5
Генерация описаний к изображениям с помощью различных архитектур нейронных сетей
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