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Contents: building models: introduction to tensorflow, introduction to computer vision, going beyond the basic: detecting features in images, using public datasets with tensorflow datasets, introduction to natural language processing, making sentiment programmable using embeddings, recurrent neu networks for natural language processing, using tensorflow ro create text, understanding sequence and time series data,creating ML models to predict sequences, using convolutional and recurrent methods for sequance models; using model: an introduction to tensorflow lite, using tensorflow lite in android apps, using tensorflow lite in IOS apps, an introduction to tensorflow.js, coding techniques for computer vision in tensorflow.js, reusing and converting python models to javascipt, transfer learning in javascipt, deployment with tensorflow serving, al ethics, and privacy