Author Archive | Jason Brownlee

Difference Between Classification and Regression in Machine Learning

Difference Between Classification and Regression in Machine Learning

There is an important difference between classification and regression problems. Fundamentally, classification is about predicting a label and regression is about predicting a quantity. I often see questions such as: How do I calculate accuracy for my regression problem? Questions like this are a symptom of not truly understanding the difference between classification and regression […]

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Encoder-Decoder Models for Text Summarization in Keras

Encoder-Decoder Models for Text Summarization in Keras

Text summarization is a problem in natural language processing of creating a short, accurate, and fluent summary of a source document. The Encoder-Decoder recurrent neural network architecture developed for machine translation has proven effective when applied to the problem of text summarization. It can be difficult to apply this architecture in the Keras deep learning […]

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What is Teacher Forcing for Recurrent Neural Networks?

What is Teacher Forcing for Recurrent Neural Networks?

Teacher forcing is a method for quickly and efficiently training recurrent neural network models that use the output from a prior time step as input. It is a network training method critical to the development of deep learning language models used in machine translation, text summarization, and image captioning, among many other applications. In this […]

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Encoder-Decoder Deep Learning Models for Text Summarization

Encoder-Decoder Deep Learning Models for Text Summarization

Text summarization is the task of creating short, accurate, and fluent summaries from larger text documents. Recently deep learning methods have proven effective at the abstractive approach to text summarization. In this post, you will discover three different models that build on top of the effective Encoder-Decoder architecture developed for sequence-to-sequence prediction in machine translation. […]

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A Gentle Introduction to Text Summarization

A Gentle Introduction to Text Summarization

Text summarization is the problem of creating a short, accurate, and fluent summary of a longer text document. Automatic text summarization methods are greatly needed to address the ever-growing amount of text data available online to both better help discover relevant information and to consume relevant information faster. In this post, you will discover the […]

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Photo of a dog at the beach.

How to Develop a Deep Learning Caption Generation Model in Keras from Scratch

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 natural language processing to turn the understanding of the image into words in the […]

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How to Use Small Experiments to Develop a Caption Generation Model in Keras

How to Use Small Experiments to Develop a Caption Generation Model in Keras

Caption generation is a challenging artificial intelligence problem where a textual description must be generated for a photograph. It requires both methods from computer vision to understand the content of the image and a language model from the field of natural language processing to turn the understanding of the image into words in the right […]

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Model 3 - Generate Word From Sequence

A Gentle Introduction to Deep Learning Caption Generation Models

Caption generation is the challenging artificial intelligence problem of generating a human-readable textual description given a photograph. It requires both image understanding from the domain of computer vision and a language model from the field of natural language processing. It is important to consider and test multiple ways to frame a given predictive modeling problem […]

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