Last Updated on August 7, 2019 Language modeling is central to many important natural language processing tasks. Recently, neural-network-based language models have demonstrated better performance than classical methods both standalone and as part of more challenging natural language processing tasks. In this post, you will discover language modeling for natural language processing. After reading this post, you will know: Why language modeling is critical to addressing tasks in natural language processing. What a language model is and some examples of […]

Last Updated on September 3, 2020 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 be used. In this tutorial, you will discover how the framing of a language model affects the skill of […]

Last Updated on September 3, 2020 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, and other document structure. This comes at the cost of requiring larger models that are slower to train. Nevertheless, […]

Last Updated on August 14, 2020 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 methods, and these days, deep learning. Deep learning methods are starting to out-compete the classical and statistical methods on […]

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 […]

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. […]

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 […]