Search results for "language model"

How to Define an Encoder-Decoder Sequence-to-Sequence Model for Neural Machine Translation in Keras

How to Develop a Seq2Seq Model for Neural Machine Translation in Keras

The encoder-decoder model provides a pattern for using recurrent neural networks to address challenging sequence-to-sequence prediction problems, such as machine translation. Encoder-decoder models can be developed in the Keras Python deep learning library and an example of a neural machine translation system developed with this model has been described on the Keras blog, with sample […]

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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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How to Develop an Encoder-Decoder Model with Attention for Sequence-to-Sequence Prediction in Keras

How to Develop an Encoder-Decoder Model with Attention in Keras

The encoder-decoder architecture for recurrent neural networks is proving to be powerful on a host of sequence-to-sequence prediction problems in the field of natural language processing such as machine translation and caption generation. Attention is a mechanism that addresses a limitation of the encoder-decoder architecture on long sequences, and that in general speeds up the […]

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A Gentle Introduction to the Bag-of-Words Model

A Gentle Introduction to the Bag-of-Words Model

The bag-of-words model is a way of representing text data when modeling text with machine learning algorithms. The bag-of-words model is simple to understand and implement and has seen great success in problems such as language modeling and document classification. In this tutorial, you will discover the bag-of-words model for feature extraction in natural language […]

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Promise of Deep Learning for Natural Language Processing

Promise of Deep Learning for Natural Language Processing

The promise of deep learning in the field of natural language processing is the better performance by models that may require more data but less linguistic expertise to train and operate. There is a lot of hype and large claims around deep learning methods, but beyond the hype, deep learning methods are achieving state-of-the-art results on […]

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7 Applications of Deep Learning for Natural Language Processing

7 Applications of Deep Learning for Natural Language Processing

The field of natural language processing is shifting from statistical methods to neural network methods. There are still many challenging problems to solve in natural language. Nevertheless, deep learning methods are achieving state-of-the-art results on some specific language problems. It is not just the performance of deep learning models on benchmark problems that is most […]

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Oxford Course on Deep Learning for Natural Language Processing

Oxford Course on Deep Learning for Natural Language Processing

Deep Learning methods achieve state-of-the-art results on a suite of natural language processing problems What makes this exciting is that single models are trained end-to-end, replacing a suite of specialized statistical models. The University of Oxford in the UK teaches a course on Deep Learning for Natural Language Processing and much of the materials for […]

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Natural Language Processing with Deep Learning

Review of Stanford Course on Deep Learning for Natural Language Processing

Natural Language Processing, or NLP, is a subfield of machine learning concerned with understanding speech and text data. Statistical methods and statistical machine learning dominate the field and more recently deep learning methods have proven very effective in challenging NLP problems like speech recognition and text translation. In this post, you will discover the Stanford […]

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