Explore how TensorFlow helps at each step of text generation: building a vocabulary, converting text to word vectors, defining and training the model, etc.
Learn how to enable long short-term memory, convolutional neural, and recurrent neural networks on top of TensorFlow to describe what is shown in the picture.
Learn how Google uses k-means for unsupervised clustering of data, stochastic dual coordinate ascent for context optimization, WALS for recommendations, etc.
The blog post scrutinizes three major phases—data preparation, training a model, and serving in production—to enable TensorFlow on top of current infrastructure.
This blog post explores a TensorFlow-based tool capable of capturing human reactions, generating a story, and evaluating the output of generative models.
Straightforwardly coded into Keras on top TensorFlow, a one-shot mechanism enables token extraction to pluck out information of interest from a data source.
