This book covers basic Python, NumPy, pandas, data visualization, and introductory TensorFlow. It is meant to provide readers with a foundation in Python-related technologies (and a very short introduction to TensorFlow) to prepare them for machine learning and related topics. Companion files with code samples, figures, etc.
eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at info@merclearning.com.
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Oswald Campesato (San Francisco, CA) specializes in Data Cleaning, Java, Android, and CSS3/SVG graphics. He is the author/co-author of over twenty-five books including Android Pocket Primer, Angular4 Pocket Primer, and the Python Pocket Primer (Mercury Learning).
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Seller: BooksRun, Philadelphia, PA, U.S.A.
Perfect Paperback. Condition: Very Good. 1. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. Seller Inventory # 1683923618-11-1
Seller: Books From California, Simi Valley, CA, U.S.A.
Paperback. Condition: Very Good. Seller Inventory # mon0002946558
Seller: Books From California, Simi Valley, CA, U.S.A.
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Seller: GreatBookPrices, Columbia, MD, U.S.A.
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Paperback or Softback. Condition: New. Python for Tensorflow Pocket Primer. Book. Seller Inventory # BBS-9781683923619
Seller: Rarewaves USA, HEBRON, KY, U.S.A.
Paperback. Condition: New. 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). Seller Inventory # LU-9781683923619
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 35907329
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Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000. Seller Inventory # L2-9781683923619
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Seller: Books Puddle, New York, NY, U.S.A.
Condition: Used. Illustrated edition NO-PA16APR2015-KAP. Seller Inventory # 26387213895