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pythondatasciencehandbook

Python Data Science Handbook: full text in Jupyter Notebooks

question-generation

Given a sentence automatically generate reading comprehension style factual questions from that sentence, such that the sentence contains answers to those questions.

restreco

scan

Sentence Constituent-Aware Aspect-Category Sentiment Analysis with Graph Attention Networks (NLPCC 2020)

scikit-learn-videos

Jupyter notebooks from the scikit-learn video series

semeval

Code for competing in some tasks in SemEval 2014

semeval-1

Code for the PRHLT participation in SemEval

semeval-2014-task-4-absa

Aspect Term Extractor for the competition SemEval-2014 Task 4 on Aspect Based Sentiment Analysis

semeval2014-competition

This is my solution to the SentEval2014 event. The event was basically a challenge to create a sentiment analysis model for twitter, and the winner was NRC-Canada

semevalaspectbasedsentimentanalysis

System that participated in Semeval 2014 task 4: Aspect Based Sentiment Analysis

sentencetriplet

Python implementation on extracting subject, predicate and object from sentences.

sentiment-lda

shdp

Nonparametric Topic Modeling with Word Vectors

t81_558_deep_learning

Washington University (in St. Louis) Course T81-558: Applications of Deep Neural Networks

target-extraction

Target based extraction

text-summarization-using-abc-optimization

topical_word_embeddings

Topical Word Embeddings

tripadvisor

TripAdvisor customer review data for brand positioning analyses. The data are of two kinds, numerical ratings that reviewers gave to hotels they stayed in, and things they said about their hotels in the form of text data. The kind of analysis that the data you'll prepare will be used for is called perceptual mapping. Different kinds of analytic methods are used to do perceptual mapping. The data is in some number json files. Each file contains data for one hotel.

twitter_hate_speech_detection

Capstone project to automate Twitter hate speech detection with classification modeling.

unsupervised-aspect-extraction

Code for acl2017 paper "An unsupervised neural attention model for aspect extraction"

ustm

vcrp

voting CRP

word-embeddings

Approximate Skip-gram word embeddings via positive pointwise mutual information and singular value decomposition

word2vec-from-scratch-with-python

A very simple, bare-bones, inefficient, implementation of skip-gram word2vec from scratch with Python

word2vec_numpy

Word2Vec implementation using numpy

wrapper-feature-selection-toolbox-python

This toolbox offers 13 wrapper feature selection methods (PSO, GA, GWO, HHO, BA, WOA, and etc.) with examples. It is simple and easy to implement.

yelp_review_analysis

Analyzed user reviews from yelp to perform natural language processing such as analyzing lexical diversity in the text, linguistic trends in various states over a time period. Identified aspects by performing sentence segmentation and tokenization, Part of Speech tagging (POS), dependency parsing and Named Entity Recognition (NER) and Latent Dirichlet Allocation algorithm (LDA) to identify topics in the corpus

zhusuan

A Library for Bayesian Deep Learning, Generative Models, Based on Tensorflow