word2vec-tsneGoogle News and Leo Tolstoy: Visualizing Word2Vec Word Embeddings using t-SNE.
Stars: ✭ 59 (+15.69%)
SentimentAnalysisSentiment Analysis: Deep Bi-LSTM+attention model
Stars: ✭ 32 (-37.25%)
datastories-semeval2017-task6Deep-learning model presented in "DataStories at SemEval-2017 Task 6: Siamese LSTM with Attention for Humorous Text Comparison".
Stars: ✭ 20 (-60.78%)
Datastories Semeval2017 Task4Deep-learning model presented in "DataStories at SemEval-2017 Task 4: Deep LSTM with Attention for Message-level and Topic-based Sentiment Analysis".
Stars: ✭ 184 (+260.78%)
NTUA-slp-nlp💻Speech and Natural Language Processing (SLP & NLP) Lab Assignments for ECE NTUA
Stars: ✭ 19 (-62.75%)
lda2vecMixing Dirichlet Topic Models and Word Embeddings to Make lda2vec from this paper https://arxiv.org/abs/1605.02019
Stars: ✭ 27 (-47.06%)
Dict2vecDict2vec is a framework to learn word embeddings using lexical dictionaries.
Stars: ✭ 91 (+78.43%)
MagnitudeA fast, efficient universal vector embedding utility package.
Stars: ✭ 1,394 (+2633.33%)
Dna2vecdna2vec: Consistent vector representations of variable-length k-mers
Stars: ✭ 117 (+129.41%)
Fasttext.jsFastText for Node.js
Stars: ✭ 127 (+149.02%)
fsauor2018基于LSTM网络与自注意力机制对中文评论进行细粒度情感分析
Stars: ✭ 36 (-29.41%)
textlyticsText processing library for sentiment analysis and related tasks
Stars: ✭ 25 (-50.98%)
neuralnets-semanticsWord semantics Deep Learning with Vanilla Python, Keras, Theano, TensorFlow, PyTorch
Stars: ✭ 15 (-70.59%)
Customer satisfaction analysis基于在线民宿 UGC 数据的意见挖掘项目,包含数据挖掘和NLP 相关的处理,负责数据采集、主题抽取、情感分析等任务。目的是克服用户打分和评论不一致,实时对在线民宿的满意度评测,包含在线评论采集和情感可视化分析。搭建了百度地图POI查询入口,可以进行自动化的批量查询 POI 信息的功能;构建了基于在线民宿语料的 LDA 自动主题聚类模型,利用主题中心词能找出对应的主题属性字典;以用户打分作为标注,然后 litNlp 自带的字符级 TextCNN 进行情感分析,将情感分类概率分布作为情感趋势,最后通过 POI 热力图的方式对不同地域的民宿满意度进行展示。软件版本请见链接。
Stars: ✭ 262 (+413.73%)
TextclfTextClf :基于Pytorch/Sklearn的文本分类框架,包括逻辑回归、SVM、TextCNN、TextRNN、TextRCNN、DRNN、DPCNN、Bert等多种模型,通过简单配置即可完成数据处理、模型训练、测试等过程。
Stars: ✭ 105 (+105.88%)
Dan Jurafsky Chris Manning NlpMy solution to the Natural Language Processing course made by Dan Jurafsky, Chris Manning in Winter 2012.
Stars: ✭ 124 (+143.14%)
wikidata-corpusTrain Wikidata with word2vec for word embedding tasks
Stars: ✭ 109 (+113.73%)
Pytorch Sentiment AnalysisTutorials on getting started with PyTorch and TorchText for sentiment analysis.
Stars: ✭ 3,209 (+6192.16%)
TwEaterA Python Bot for Scraping Conversations from Twitter
Stars: ✭ 16 (-68.63%)
Sarcasm DetectionDetecting Sarcasm on Twitter using both traditonal machine learning and deep learning techniques.
Stars: ✭ 73 (+43.14%)
word-embeddings-from-scratchCreating word embeddings from scratch and visualize them on TensorBoard. Using trained embeddings in Keras.
Stars: ✭ 22 (-56.86%)
two-stream-cnnA two-stream convolutional neural network for learning abitrary similarity functions over two sets of training data
Stars: ✭ 24 (-52.94%)
empythyAutomated NLP sentiment predictions- batteries included, or use your own data
Stars: ✭ 17 (-66.67%)
KoanA word2vec negative sampling implementation with correct CBOW update.
Stars: ✭ 232 (+354.9%)
Text mining resourcesResources for learning about Text Mining and Natural Language Processing
Stars: ✭ 358 (+601.96%)
LanguagecrunchLanguageCrunch NLP server docker image
Stars: ✭ 281 (+450.98%)
twitter-aws-comprehendAn app to analyze tweets using Amazon Comprehend's Sentiment Analysis service
Stars: ✭ 13 (-74.51%)
Cw2veccw2vec: Learning Chinese Word Embeddings with Stroke n-gram Information
Stars: ✭ 224 (+339.22%)
Doc2vec📓 Long(er) text representation and classification using Doc2Vec embeddings
Stars: ✭ 92 (+80.39%)
Repo 2017Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano
Stars: ✭ 1,123 (+2101.96%)
Onnxt5Summarization, translation, sentiment-analysis, text-generation and more at blazing speed using a T5 version implemented in ONNX.
Stars: ✭ 143 (+180.39%)
Textblob ArArabic support for textblob
Stars: ✭ 60 (+17.65%)
QuestionClusteringClasificador de preguntas escrito en python 3 que fue implementado en el siguiente vídeo: https://youtu.be/qnlW1m6lPoY
Stars: ✭ 15 (-70.59%)
SensegramMaking sense embedding out of word embeddings using graph-based word sense induction
Stars: ✭ 209 (+309.8%)
Paribhashaparibhasha.herokuapp.com/
Stars: ✭ 21 (-58.82%)
Entity EmbeddingReference implementation of the paper "Word Embeddings for Entity-annotated Texts"
Stars: ✭ 19 (-62.75%)
SentimentAnalysis(BOW, TF-IDF, Word2Vec, BERT) Word Embeddings + (SVM, Naive Bayes, Decision Tree, Random Forest) Base Classifiers + Pre-trained BERT on Tensorflow Hub + 1-D CNN and Bi-Directional LSTM on IMDB Movie Reviews Dataset
Stars: ✭ 40 (-21.57%)
DeepLearningReadingDeep Learning and Machine Learning mini-projects. Current Project: Deepmind Attentive Reader (rc-data)
Stars: ✭ 78 (+52.94%)
PersianNERNamed-Entity Recognition in Persian Language
Stars: ✭ 48 (-5.88%)
ml-bookCodice sorgente ed Errata Corrige del mio libro "A tu per tu col Machine Learning"
Stars: ✭ 16 (-68.63%)
word-benchmarksBenchmarks for intrinsic word embeddings evaluation.
Stars: ✭ 45 (-11.76%)
word2vec-on-wikipediaA pipeline for training word embeddings using word2vec on wikipedia corpus.
Stars: ✭ 68 (+33.33%)
ar-embeddingsSentiment Analysis for Arabic Text (tweets, reviews, and standard Arabic) using word2vec
Stars: ✭ 83 (+62.75%)
ShallowlearnAn experiment about re-implementing supervised learning models based on shallow neural network approaches (e.g. fastText) with some additional exclusive features and nice API. Written in Python and fully compatible with Scikit-learn.
Stars: ✭ 196 (+284.31%)
Chameleon recsysSource code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems
Stars: ✭ 202 (+296.08%)