Search results for "word embedding"

What Are Word Embeddings for Text?

What Are Word Embeddings for Text?

Word embeddings are a type of word representation that allows words with similar meaning to have a similar representation. They are a distributed representation for text that is perhaps one of the key breakthroughs for the impressive performance of deep learning methods on challenging natural language processing problems. In this post, you will discover the […]

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Scatter Plot of PCA Projection of Word2Vec Model

How to Develop Word Embeddings in Python with Gensim

Word embeddings are a modern approach for representing text in natural language processing. Word embedding algorithms like word2vec and GloVe are key to the state-of-the-art results achieved by neural network models on natural language processing problems like machine translation. In this tutorial, you will discover how to train and load word embedding models for natural […]

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How to Use Word Embedding Layers for Deep Learning with Keras

How to Use Word Embedding Layers for Deep Learning with Keras

Word embeddings provide a dense representation of words and their relative meanings. They are an improvement over sparse representations used in simpler bag of word model representations. Word embeddings can be learned from text data and reused among projects. They can also be learned as part of fitting a neural network on text data. In this […]

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How to Develop a Word-Level Neural Language Model and Use it to Generate Text

How to Develop a Word-Level Neural Language Model and Use it to Generate Text

A language model can predict the probability of the next word in the sequence, based on the words already observed in the sequence. Neural network models are a preferred method for developing statistical language models because they can use a distributed representation where different words with similar meanings have similar representation and because they can […]

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How to Develop Word-Based Neural Language Models in Python with Keras

How to Develop Word-Based Neural Language Models in Python with Keras

Language modeling involves predicting the next word in a sequence given the sequence of words already present. A language model is a key element in many natural language processing models such as machine translation and speech recognition. The choice of how the language model is framed must match how the language model is intended to […]

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How to Develop a Deep Learning Bag-of-Words Model for Predicting Sentiment in Movie Reviews

How to Develop a Deep Learning Bag-of-Words Model for Sentiment Analysis (Text Classification)

Movie reviews can be classified as either favorable or not. The evaluation of movie review text is a classification problem often called sentiment analysis. A popular technique for developing sentiment analysis models is to use a bag-of-words model that transforms documents into vectors where each word in the document is assigned a score. In this […]

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Photo of a dog at the beach.

How to Develop a Deep Learning Photo Caption Generator from Scratch

Develop a Deep Learning Model to Automatically Describe Photographs in Python with Keras, Step-by-Step. Caption generation is a challenging artificial intelligence problem where a textual description must be generated for a given photograph. It requires both methods from computer vision to understand the content of the image and a language model from the field of […]

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