A Gentle Introduction to Calculating the BLEU Score for Text in Python

A Gentle Introduction to Calculating the BLEU Score for Text in Python

BLEU, or the Bilingual Evaluation Understudy, is a score for comparing a candidate translation of text to one or more reference translations. Although developed for translation, it can be used to evaluate text generated for a suite of natural language processing tasks. In this tutorial, you will discover the BLEU score for evaluating and scoring […]

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How to Prepare Univariate Time Series Data for Long Short-Term Memory Networks

How to Prepare Univariate Time Series Data for Long Short-Term Memory Networks

It can be hard to prepare data when you’re just getting started with deep learning. Long Short-Term Memory, or LSTM, recurrent neural networks expect three-dimensional input in the Keras Python deep learning library. If you have a long sequence of thousands of observations in your time series data, you must split your time series into […]

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How to Prepare a Photo Caption Dataset for Training a Deep Learning Model

How to Prepare a Photo Caption Dataset for Training a Deep Learning Model

Automatic photo captioning is a problem where a model must generate a human-readable textual description given a photograph. It is a challenging problem in artificial intelligence that requires both image understanding from the field of computer vision as well as language generation from the field of natural language processing. It is now possible to develop […]

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Example of annotation regions of an image with descriptions

How to Automatically Generate Textual Descriptions for Photographs with Deep Learning

Captioning an image involves generating a human readable textual description given an image, such as a photograph. It is an easy problem for a human, but very challenging for a machine as it involves both understanding the content of an image and how to translate this understanding into natural language. Recently, deep learning methods have […]

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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 Get Started with Deep Learning for Natural Language Processing

How to Get Started with Deep Learning for Natural Language Processing

Deep Learning for NLP Crash Course. Bring Deep Learning methods to Your Text Data project in 7 Days. We are awash with text, from books, papers, blogs, tweets, news, and increasingly text from spoken utterances. Working with text is hard as it requires drawing upon knowledge from diverse domains such as linguistics, machine learning, statistical […]

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How to Develop a Character-Based Neural Language Model in Keras

How to Develop a Character-Based Neural Language Model in Keras

A language model predicts the next word in the sequence based on the specific words that have come before it in the sequence. It is also possible to develop language models at the character level using neural networks. The benefit of character-based language models is their small vocabulary and flexibility in handling any words, punctuation, […]

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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 an Encoder-Decoder Model for Sequence-to-Sequence Prediction in Keras

How to Develop an Encoder-Decoder Model for Sequence-to-Sequence Prediction 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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