Notes:
- Distributional semantic model
- Distributed representation
- Neural word embedding
- Semantic vector space
- Vector space model
- Word vectors
Resources:
- eigenwords .. eigenword resource page
- gensim .. easy to build prototypes with various models
- glove .. an unsupervised learning algorithm for obtaining vector representations for words
- tensorflow word2vec tutorial .. used for learning vector representations of words, called “word embeddings”
- word2vec .. an implementation of the continuous bag-of-words (cbow) and the skip-gram model (sg)
- word2vec in java .. neural word embeddings in java and scala
- wordvectors.org .. you can upload the filtered vectors
Wikipedia:
See also:
100 Best Word2vec Videos | Word2vec & Dialog Systems 2016
- Webinar on Word Embeddings | HackerEarth
- Data Mining Lab – Word Embeddings (Part 2)
- Data Mining Lab – Word Embeddings (Part 1)
- Word Sense Disambiguation on Linguistic Regularity and Classification Accuracy of Word Embeddings
- Use of word embedding algorithms and siamese recurrent neural networks
- Datageeks Data Day 2017 – Fabian Dill – Word Embeddings – Part 1 of 2
- Datageeks Data Day 2017 – Fabian Dill – Word Embeddings – Part 2 of 2
- Word Embeddings II
- ADLxMLDS Lecture 4: Word Embeddings (17/10/16 + 17/10/23)
- Debiasing Word Embeddings
- WORD EMBEDDINGS
- ADLxMLDS Lecture 4: Word Embeddings (17/10/19)
- Word Embeddings I
- Collaboratively Improving Topic Discovery and Word Embeddings
- Meetup #30 – Piero Molino: Word Embeddings – Past, Present and Future
- Big Data and Info Retrieval Lecture 5 (171012) – word embedding vis, RNNs
- Word Embedding Models (Lecture 7; October 4, 2017)
- Big Data and Info Retrieval Lecture 4 (170928) – word embedding
- Big Data and Info Retrieval Lecture 3 (170921) – topic modeling, word embedding
- Domain Specific Word Embedding for Cybersecurity Text by Roy Arpita
- Learning to Compute Word Embeddings On the Fly by Dzmitry Bahdanau
- Marco Bonzanini – Word Embeddings for Natural Language Processing in Python
- Word Embeddings for Natural Language Processing in Python – MARCO BONZANINI
- Dynamic Word Embeddings
- Lev Konstantinovskiy – Text similiarity with the next generation of word embeddings in Gensim
- Word Embeddings
- A tool kit for query the document, word embedding
- Marco Bonzanini – Word Embeddings for Natural Language Processing in Python
- Collaboratively Improving Topic Discovery and Word Embeddings
- June 20: practical AI workshop – Rachel Thomas, word embeddings and data biases
- Machine Learning Project 4: Gender Bias in Word Embeddings
- Word Embeddings, Bias in ML, Why You Don’t Like Math, & Why AI Needs You
- Learn how to say this word: “Embedding”
- ConceptVector: Building User-Driven Concepts via Word Embedding
- Piero Molino- Word Embeddings: History, Present and Future AIWTB 2017
- Lev Konstantinovskiy – Next generation of word embeddings in Gensim
- Text Similarity Based on Word Embeddings, Syntax Trees
- What is WORD EMBEDDING? What does WORD EMBEDDING mean? WORD EMBEDDING meaning & explanation
- Lev Konstaninovskiy – Word Embedding For Fun and Profit
- Word-Embedding-Enhanced Alexa Skill on an Echo – Demo
- Representations for Language: From Word Embeddings to Sentence Meanings
- D2L4 Word Embeddings – Word2Vec (by Antonio Bonafonte)
- Word Embeddings applied to Nao’s speech
- Acoustic word embeddings
- Introdução aos Word Embeddings
- contextual word embeddings for recomendor systems by Akhil Gupta 36:18
- 20161221 neural network word embedding backward
- 20161220 neural network onehot word embedding
- ML Lecture 14: Unsupervised Learning – Word Embedding
- James Thorne – A Convolution Kernel for Sentiment Analysis using Word-Embeddings
- Document and Word Embeddings for Text Mining
- Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images
- Actionable and Political Text Classification Using Word Embeddings and LSTM
- Decoding Fashion Contexts Using Word Embeddings
- Unsupervised Word Segmentation and Lexicon Discovery Using Acoustic Word Embeddings
- Word embedding in Spanish at Universidad Nacional Colombia 2016
- Martin Jaggi – Deep Learning for Text – From Word Embeddings to Convolutional Neural Networks
- Introduction to Word Embeddings
- Lev Konstantinovskiy – Word Embeddings for fun and profit in Gensim
- Word Embedding Explained and Visualized – word2vec and wevi
- Revisiting Word Embedding for Contrasting Meaning
- Specializing Word Embeddings for Similarity or Relatedness
- Francois Scharffe: Word embeddings as a service
- Dependency-based word embeddings
- Word: Embedding a Video
- BDSBTB 2015: Marek Kolodziej, Unsupervised NLP Using Word Embeddings, Scala and Apache Spark
- Word Embedding: from theory to practice
- Stockholm NLP Meetup: Word Embedding from Theory to Practice
- Excel Tutorial: Excel Word embedding | ExcelCentral.com
- Microsoft Word: Embedding files in your document. AOTraining.net