Python for TensorFlow Pocket Primer

Oswald Campesato

ISBN 10: 1683923618 / ISBN 13: 9781683923619

Verlag: Mercury Learning And Information, De Gruyter, 2019

Beschreibung

nach der Bestellung gedruckt Neuware - Printed after ordering - No detailed description available for 'Python for TensorFlow Pocket Primer'. Bestandsnummer des Verkäufers 9781683923619

Bibliografische Details

Titel: Python for TensorFlow Pocket Primer

Verlag: Mercury Learning And Information, De Gruyter

Erscheinungsdatum: 2019

Einband: Taschenbuch

Zustand: Neu

Über diesen Titel

Reseña del editor:

As part of the best-selling Pocket Primer series, this book is designed to prepare programmers for machine learning and deep learning/TensorFlow topics. It begins with a quick introduction to Python, followed by chapters that discuss NumPy, Pandas, Matplotlib, and scikit-learn. The final two chapters contain an assortment of TensorFlow 1.x code samples, including detailed code samples for TensorFlow Dataset (which is used heavily in TensorFlow 2 as well). A TensorFlow Dataset refers to the classes in the tf.data.Dataset namespace that enables programmers to construct a pipeline of data by means of method chaining so-called lazy operators, e.g., map(), filter(), batch(), and so forth, based on data from one or more data sources. Companion files with source code are available for downloading from the publisher. FEATURES, A practical introduction to Python, NumPy, Pandas, Matplotlib, and introductory aspects of TensorFlow 1.x, Contains relevant NumPy/Pandas code samples that are typical in machine learning topics, and also useful TensorFlow 1.x code samples for deep learning/TensorFlow topics, Includes many examples of TensorFlow Dataset APIs with lazy operators, e.g., map(), filter(), batch(), take() and also method chaining such operators, Assumes the reader has very limited experience, Includes companion files with all of the source code examples (download from the publisher).