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.
In addition to cloud hype and blockchain focus, the major IBM event highlighted how IoT, AI, and machine learning are having an impact on multiple industries.
This blog post explores a TensorFlow-based tool capable of capturing human reactions, generating a story, and evaluating the output of generative models.
