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Graph Representation Learning Book
Introduction to graph representation learning, including methods for embedding graph data, graph neural networks, and deep generative models of graphs.
graph-representation-learning graph-neural-networks knowledge-graphs book
Tips for Successfully Training Transformers on Small Datasets
It turns out that you can easily train transformers on small datasets when you use tricks (and have the patience to train a very long time).
transformers small-datasets training ptb
Top2Vec learns jointly embedded topic, document and word vectors.
topic-modeling document-embeddings word-embeddings embeddings
Universal Sentence Encoder Visually Explained
A deep-dive into how Universal Sentence Encoder learns to generate fixed-length sentence embeddings
sentence-embeddings tensorflow natural-language-processing embeddings
Lda2vec: Tools for interpreting natural language
The lda2vec model tries to mix the best parts of word2vec and LDA into a single framework.
topic-modeling latent-dirichlet-allocation word2vec embeddings
A Visual Guide to FastText Word Embeddings
A deep-dive into how FastText enriches word vectors with sub-word information
natural-language-processing word-embeddings fasttext embeddings
The Illustrated Word2vec
In this post, we’ll go over the concept of embedding, and the mechanics of generating embeddings with word2vec.
word-embeddings embeddings word2vec video
Interactive Analysis of Sentence Embeddings
Learn how to interactively explore sentence embedding and labels in Tensorflow Embedding Projector.
natural-language-processing tensorflow-js contextualized-embeddings embeddings
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