Articles About Machine Learning

How to Use The Pre-Trained VGG Model to Classify Objects in Photographs

Last Updated on August 19, 2019 Convolutional neural networks are now capable of outperforming humans on some computer vision tasks, such as classifying images. That is, given a photograph of an object, answer the question as to which of 1,000 specific objects the photograph shows. A competition-winning model for this task is the VGG model by researchers at Oxford. What is important about this model, besides its capability of classifying objects in photographs, is that the model weights are freely […]

Read more

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

Last Updated on September 3, 2020 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 use a large context of recently observed words when making predictions. In this tutorial, you will discover how to […]

Read more

How to Automatically Generate Textual Descriptions for Photographs with Deep Learning

Last Updated on August 7, 2019 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 displaced classical methods and are achieving state-of-the-art results for the problem of automatically generating descriptions, called “captions,” for images. […]

Read more

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

Last Updated on August 7, 2019 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 your own image caption models using deep learning and freely available datasets of photos and their descriptions. In this […]

Read more

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

Last Updated on August 5, 2019 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 samples and then reshape it for your LSTM model. In this tutorial, you will discover exactly how to prepare […]

Read more

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

Last Updated on December 19, 2019 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 candidate text using the NLTK library in Python. After completing this tutorial, you will know: A gentle introduction to […]

Read more

A Gentle Introduction to Deep Learning Caption Generation Models

Last Updated on August 7, 2019 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 and there are indeed many ways to frame the problem of generating captions for photographs. In this tutorial, you […]

Read more

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

Last Updated on September 3, 2020 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 order. Recently, deep learning methods have achieved state of the art results on examples of this problem. It can […]

Read more

A Gentle Introduction to Text Summarization

Last Updated on August 7, 2019 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 problem of text summarization in natural language processing. After reading this post, you will know: Why text summarization is […]

Read more

Encoder-Decoder Deep Learning Models for Text Summarization

Last Updated on August 7, 2019 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. After reading this post, you will know: The Facebook AI Research model that uses the Encoder-Decoder model with a […]

Read more
1 169 170 171 172 173 226