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Search results for jupyter notebook glove
glove
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jupyter-notebook
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64 search results found
Cs224u
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2,007
Code for Stanford CS224u
Cs224n Squad Project
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389
Keras Quora Question Pairs
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357
A Keras model that addresses the Quora Question Pairs dyadic prediction task.
Tensorflow Glove
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280
An implementation of GloVe in TensorFlow
Bnlp
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252
BNLP is a natural language processing toolkit for Bengali Language.
Leam
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236
2018 Daguan Competition
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230
2018年"达观杯"文本智能处理挑战赛-长文本分类-rank4
Text_similarity
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189
Text Similarity
Hierarchical Attention Network
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117
Implementation of Hierarchical Attention Networks in PyTorch
Nlp_adversarial_examples
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112
Implementation code for the paper "Generating Natural Language Adversarial Examples"
Selfattentive
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108
Implementation of A Structured Self-attentive Sentence Embedding
Deep Learning Interview
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100
深度学习面试汇总,基本知识点的查漏补缺
Image Captions
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77
BERT + Image Captioning
Toxic Comment Classification
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72
Code and write-up for the Kaggle Toxic Comment Classification Challenge
Cn Words
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55
Get Similar Chinese Words and Sentences
Word Embedding With Python
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52
word2vec, doc2vec, GloVe implementation with Python
Turkish Tweets Sentiment Analysis
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52
This sentiment analysis project determines whether the tweets posted in the Turkish language on Twitter are positive or negative.
Turkish Glove
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51
Türkçe GloVe - Repository for Turkish GloVe Word Embeddings
Poincare_glove
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37
Implementation of the "Poincare Glove: Hyperbolic word embeddings" paper
Kdd2018
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35
Hands-on workshop
Aspect Based Sentiment Analysis
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27
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.
Servenet
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24
Service Classification based on Service Description
Nlp Practice With Tensorflow2
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23
使用tensorflow2完成一些常见的NLP任务
Cmu Multimodalsdk Tutorials
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21
This is a short tutorial for using the CMU-MultimodalSDK.
W2vsenti_sentiment Word Embedding Based On W2v
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21
graduation project : sentiment analysis with different word-embeddings @ huxi
Visual Question Answering
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20
📷 ❓ Visual Question Answering Demo and Algorithmia API
Podcast Recommendation Engine
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19
🎤 Building a content-based podcast recommender system using NLP
Nyyelp
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18
predicting yelp review rating using recurrent neural networks
Sentiment Analysis Pytorch
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18
Sentiment analysis in Pytorch on an IMDb dataset.
Fake News Classification Model
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16
✨ Fake news classification using source adaptive framework - BE Project 🎓The repository contains Detailed Documentation of the project, Classification pipeline, Architecture, System Interface Design, Tech stack used.
Emojify
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13
Emojify uses ML Models to create Emoji's corresponding to a given sentence.
Spotify Skip Prediction Top 1 Solution
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13
Midi Glove
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13
Create MIDI note vector embeddings using GloVe (Global Vectors for Word Representation)
Textsummarizer
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12
Text Summarizer implementation with Tensorflow 2.0 using conditional GAN
Gender_bias_lipstick
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12
Lavse
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11
Language-Agnostic Visual-Semantic Embeddings (ICCV'19)
Hyperbolic_zsl
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10
Hyperbolic Visual Embedding Learning for Zero-Shot Recognition (CVPR 2020)
Artificial Vision And Language Processing For Robotics
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10
Keyword_i2x
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10
Generates the most important key-phrase/key-words from a document based on a corpus
Nlp_programs
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9
本repo使用tensorflow2实现NLP中常见的模型:文本相似度分析、文本摘要、文本生成、机器
Wordembeddings
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9
Some experimentations with word embeddings
Twitter_sentiment_analysis_part10
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9
Twitter sentiment analysis part 9: Neural Networks with Doc2Vec, Word2Vec, GloVe
Playground
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8
store my personal project
Fake News Stance Detection
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8
Checks for the Stance detection in a unlabeled news dataset.
Burvec
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8
Word Embeddings for Low Resource Languages: The Case of Buryat
Debot
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7
Twitter bot detection using deep learning.
Doc2vec_cqadupstack
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7
Code for reproducing J Lau's doc2vec results on CQADupStack
Capsnet_for_ner
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7
Adapt Capsule Network for Name Entity Recognition Task
Machine Comprehension Keras
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7
SimpleQA for SQuAd Dataset
Compare_word_embedding
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7
意味表現学習
Twitter Stance Classification By Tensorflow
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7
Movie Review Classification
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6
Predicted IMDB movie review polarity in Python with GloVe word embedding and XGBoost model.
Twitterstudiescode
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6
Quora_test
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6
Quick Pytorch attempt at the quora kaggle challende
Bcn Cnn Text Classification
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6
Text classification experiments using TextCNNs and Bi-attentive Classification Networks
Semantic Text Segmentation With Embeddings
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6
Uses GloVe embeddings and greedy sequence segmentation to semantically segment a text document into any number of k segments.
Masters Thesis Ml
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5
Repository for my master's thesis in machine learning at UiB
Deep Learning For Natural Language Processing
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5
Solve your natural language processing problems with smart deep neural networks
Sentiment Analysis With Word Embeddings
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5
A Sentiment Analysis model in keras to analyse toxic comments online . The Corpus is preprocessed using Glove Word Embeddings .
Faquad
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5
FaQuAD reading comprehension dataset and related code to reproduce experiments from Sayama et al. (BRACIS 2019).
Deepdeco
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5
Generate customizable interior design images with sketches and text description.
Quora Question Similarity Using Bert Embeddings With Siamese Networks As Feature Extractors
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5
Proposed a model architecture which learns to classify duplicate question pairs based on highly contextualized sentence representations. Achieved by using both individual and combined sentence embeddings based on Word2Vec, GloVe and FastText word embeddings with CNN(convolutional neural networks) and DNN(Dense neural network) Siamese networks and an array of features engineered using sentence structure, fuzzy logic , BERT sentence embeddings and BERT [CLS] token.
Tokenization And Word Embedding Compatibility
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5
The Quora Insincere Question Classification competition allows us to use the four embeddings: glove.840B.300d (GloVe), paragram_300_sl999 (paragram), wiki-news-300d-1M (wiki) and GoogleNews-vectors-negative300 (GoogleNews). In a kernel titled: "How to: Preprocessing when Using Embeddings", the author raises the issue of tokenization and its effect on how much of the training vocabulary is covered by words in an embedding. The author uses Google news embeddings to illustrate this point. In this k
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