More flexible models with TensorFlow eager execution and Keras
Advanced applications like generative adversarial networks, neural style transfer, and the attention mechanism ubiquitous in natural language processi…
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Collaborative filtering with embeddings
Embeddings are not just for use in natural language processing. Here we apply embeddings to a common task in collaborative filtering - predicting user…
Image-to-image translation with pix2pix
Conditional GANs (cGANs) may be used to generate one type of object based on another - e.g., a map based on a photo, or a color video based on black-a…
Attention-based Image Captioning with Keras
Image captioning is a challenging task at intersection of vision and language. Here, we demonstrate using Keras and eager execution to incorporate an …
Neural style transfer with eager execution and Keras
Continuing our series on combining Keras with TensorFlow eager execution, we show how to implement neural style transfer in a straightforward way. Bas…
Getting started with deep learning in R
Many fields are benefiting from the use of deep learning, and with the R keras, tensorflow and related packages, you can now easily do state of the ar…
Generating images with Keras and TensorFlow eager execution
Generative adversarial networks (GANs) are a popular deep learning approach to generating new entities (often but not always images). We show how to c…
Attention-based Neural Machine Translation with Keras
As sequence to sequence prediction tasks get more involved, attention mechanisms have proven helpful. A prominent example is neural machine translatio…
Classifying physical activity from smartphone data
Using Keras to train a convolutional neural network to classify physical activity. The dataset was built from the recordings of 30 subjects performing…
Predicting Sunspot Frequency with Keras
In this post we will examine making time series predictions using the sunspots dataset that ships with base R. Sunspots are dark spots on the sun, ass…
