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As sequence to sequence prediction tasks get more involved, attention mechanisms have proven helpful. A prominent example is neural machine translation. Following a recent Google Colaboratory notebook, we show how to implement attention in R.
Attention-based Neural Machine Translation with Keras Read More »
Image captioning is a challenging task at intersection of vision and language. Here, we demonstrate using Keras and eager execution to incorporate an attention mechanism that allows the network to concentrate on image features relevant to the current state of text generation.
Two-class classification, or binary classification, may be the most widely applied kind of machine-learning problem. In this excerpt from the book Deep Learning with R, you’ll learn to classify movie reviews as positive or negative, based on the text content of the reviews.
Deep Learning for Text Classification with Keras Read More »
Word embedding is a method used to map words of a vocabulary to dense vectors of real numbers where semantically similar words are mapped to nearby points. In this example we’ll use Keras to generate word embeddings for the Amazon Fine Foods Reviews dataset.
In this post we will use Keras to classify duplicated questions from Quora. Our implementation is inspired by the Siamese Recurrent Architecture, with modifications to the similarity measure and the embedding layers (the original paper uses pre-trained word vectors)
Classifying Duplicate Questions from Quora with Keras Read More »
The kerasformula package offers a high-level interface for the R interface to Keras. It’s main interface is the kms function, a regression-style interface to keras_model_sequential that uses formulas and sparse matrices. We use kerasformula to predict how popular tweets will be based on how often the tweet was retweeted and favorited.
We introduce StreetReaderAI, a new accessible street view prototype using context-aware, real-time AI and accessible navigation controls. Interactive streetscape tools, available today in every major mapping service, have revolutionized how people virtually navigate and explore the world — from previewing routes and inspecting destinations to remotely visiting world-class tourist locations. But to date, screen readers
StreetReaderAI: Towards making street view accessible via context-aware multimodal AI Read More »
DS-STAR is a state-of-the-art data science agent whose versatility is shown by its ability to automate a range of tasks — from statistical analysis to visualization and data wrangling — across various data types, culminating in a top-ranking performance on the famous DABStep benchmark. Data science is a field dedicated to transforming raw data into
DS-STAR: A state-of-the-art versatile data science agent Read More »
Voice Search is now powered by our new Speech-to-Retrieval engine, which gets answers straight from your spoken query without having to convert it to text first, resulting in a faster, more reliable search for everyone. Voice-based web search has been around a long time and continues to be used by many people, with the underlying
Speech-to-Retrieval (S2R): A new approach to voice search Read More »
