Nlp In PracticeStarter code to solve real world text data problems. Includes: Gensim Word2Vec, phrase embeddings, Text Classification with Logistic Regression, word count with pyspark, simple text preprocessing, pre-trained embeddings and more.
Stars: ✭ 790 (+230.54%)
TadwAn implementation of "Network Representation Learning with Rich Text Information" (IJCAI '15).
Stars: ✭ 43 (-82.01%)
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 (-17.99%)
GermanwordembeddingsToolkit to obtain and preprocess german corpora, train models using word2vec (gensim) and evaluate them with generated testsets
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Word2vec訓練中文詞向量 Word2vec, Word2vec was created by a team of researchers led by Tomas Mikolov at Google.
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Log Anomaly DetectorLog Anomaly Detection - Machine learning to detect abnormal events logs
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Nlp NotebooksA collection of notebooks for Natural Language Processing from NLP Town
Stars: ✭ 513 (+114.64%)
Text2vecFast vectorization, topic modeling, distances and GloVe word embeddings in R.
Stars: ✭ 715 (+199.16%)
Word2vec Russian NovelsInspired by word2vec-pride-vis the replacement of words of Russian most valuable novels text with closest word2vec model words. By Boris Orekhov
Stars: ✭ 39 (-83.68%)
wordfish-pythonextract relationships from standardized terms from corpus of interest with deep learning 🐟
Stars: ✭ 19 (-92.05%)
NlpythonThis repository contains the code related to Natural Language Processing using python scripting language. All the codes are related to my book entitled "Python Natural Language Processing"
Stars: ✭ 265 (+10.88%)
ServenetService Classification based on Service Description
Stars: ✭ 21 (-91.21%)
BagofconceptsPython implementation of bag-of-concepts
Stars: ✭ 18 (-92.47%)
Deeplearning Nlp ModelsA small, interpretable codebase containing the re-implementation of a few "deep" NLP models in PyTorch. Colab notebooks to run with GPUs. Models: word2vec, CNNs, transformer, gpt.
Stars: ✭ 64 (-73.22%)
Sense2vec🦆 Contextually-keyed word vectors
Stars: ✭ 1,184 (+395.4%)
Text Analytics With PythonLearn how to process, classify, cluster, summarize, understand syntax, semantics and sentiment of text data with the power of Python! This repository contains code and datasets used in my book, "Text Analytics with Python" published by Apress/Springer.
Stars: ✭ 1,132 (+373.64%)
Python nlp tutorialThis repository provides everything to get started with Python for Text Mining / Natural Language Processing (NLP)
Stars: ✭ 72 (-69.87%)
MagnitudeA fast, efficient universal vector embedding utility package.
Stars: ✭ 1,394 (+483.26%)
Awesome Embedding ModelsA curated list of awesome embedding models tutorials, projects and communities.
Stars: ✭ 1,486 (+521.76%)
Text-AnalysisExplaining textual analysis tools in Python. Including Preprocessing, Skip Gram (word2vec), and Topic Modelling.
Stars: ✭ 48 (-79.92%)
Product-Categorization-NLPMulti-Class Text Classification for products based on their description with Machine Learning algorithms and Neural Networks (MLP, CNN, Distilbert).
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word2vec-pt-brImplementação e modelo gerado com o treinamento (trigram) da wikipedia em pt-br
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Deep learning nlpKeras, PyTorch, and NumPy Implementations of Deep Learning Architectures for NLP
Stars: ✭ 407 (+70.29%)
Lmdb EmbeddingsFast word vectors with little memory usage in Python
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WebvectorsWeb-ify your word2vec: framework to serve distributional semantic models online
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Crime AnalysisAssociation Rule Mining from Spatial Data for Crime Analysis
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lda2vecMixing Dirichlet Topic Models and Word Embeddings to Make lda2vec from this paper https://arxiv.org/abs/1605.02019
Stars: ✭ 27 (-88.7%)
SplitterA Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).
Stars: ✭ 177 (-25.94%)
Nlp profilerA simple NLP library allows profiling datasets with one or more text columns. When given a dataset and a column name containing text data, NLP Profiler will return either high-level insights or low-level/granular statistical information about the text in that column.
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ExperimentsSome research experiments
Stars: ✭ 95 (-60.25%)
ScattertextBeautiful visualizations of how language differs among document types.
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Nlp JourneyDocuments, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation),etc. All codes are implemented intensorflow 2.0.
Stars: ✭ 1,290 (+439.75%)
Role2vecA scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018).
Stars: ✭ 134 (-43.93%)
Ml ProjectsML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python
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Textfeatures👷♂️ A simple package for extracting useful features from character objects 👷♀️
Stars: ✭ 148 (-38.08%)
Glove As A Tensorflow Embedding LayerTaking a pretrained GloVe model, and using it as a TensorFlow embedding weight layer **inside the GPU**. Therefore, you only need to send the index of the words through the GPU data transfer bus, reducing data transfer overhead.
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DebiasweRemove problematic gender bias from word embeddings.
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Deep Math Machine Learning.aiA blog which talks about machine learning, deep learning algorithms and the Math. and Machine learning algorithms written from scratch.
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Gwu data miningMaterials for GWU DNSC 6279 and DNSC 6290.
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walkletsA lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).
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RolXAn alternative implementation of Recursive Feature and Role Extraction (KDD11 & KDD12)
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MusaeThe reference implementation of "Multi-scale Attributed Node Embedding".
Stars: ✭ 75 (-68.62%)
GensimTopic Modelling for Humans
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GemsecThe TensorFlow reference implementation of 'GEMSEC: Graph Embedding with Self Clustering' (ASONAM 2019).
Stars: ✭ 210 (-12.13%)
Practical 1Oxford Deep NLP 2017 course - Practical 1: word2vec
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