As part of the best-selling PocketPrimer series, this book is designed to prepare programmersfor machine learning and deep learning/TensorFlow topics. It begins with aquick introduction to Python, followed by chapters that discuss NumPy, Pandas,Matplotlib, and scikit-learn. The final two chapters contain an assortment ofTensorFlow 1.x code samples, including detailed code samples for TensorFlowDataset (which is used heavily in TensorFlow 2 as well). A TensorFlow Datasetrefers to the classes in the tf.data.Dataset namespace that enables programmersto construct a pipeline of data by means of method chaining so-called lazyoperators, e.g., map(), filter(), batch(), and so forth, based on data from oneor more data sources.
Companion files with source code areavailable for downloading from the publisher by writing info@merclearning.com.
Features:
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Campesato Oswald :
Oswald Campesato (San Francisco, CA) is an adjunct instructor at UC-Santa Clara and specializes in Deep Learning, Java, Android, TensorFlow, and NLP. He is the author/co-author of over twenty-five books including TensorFlow 2 Pocket Primer, Python 3 for Machine Learning, and the NLP Using R Pocket Primer (all Mercury Learning and Information).
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