Python for TensorFlow Pocket Primer / / Oswald Campesato.
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 chapter...
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Place / Publishing House: | Dulles, VA : : Mercury Learning and Information, , [2019] ©2019 |
Year of Publication: | 2019 |
Language: | English |
Series: | Pocket Primer
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Physical Description: | 1 online resource (218 p.) |
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Campesato, Oswald, author. aut http://id.loc.gov/vocabulary/relators/aut Python for TensorFlow Pocket Primer / Oswald Campesato. Dulles, VA : Mercury Learning and Information, [2019] ©2019 1 online resource (218 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda Pocket Primer Frontmatter -- Contents -- Preface -- Chapter 1. Introduction to Python -- Chapter 2. Introduction to NumPy -- Chapter 3. Introduction to Pandas -- Chapter 4. Matplotlib, Sklearn, and Seaborn -- Chapter 5. Introduction to TensorFlow -- Chapter 6. TensorFlow Datasets -- Index restricted access http://purl.org/coar/access_right/c_16ec online access with authorization star 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 by writing info@merclearning.com. Features:A practical introduction to Python, NumPy, Pandas, Matplotlib, and introductory aspects of TensorFlow 1.xContains relevant NumPy/Pandas code samples that are typical in machine learning topics, and also useful TensorFlow 1.x code samples for deep learning/TensorFlow topicsIncludes many examples of TensorFlow Dataset APIs with lazy operators, e.g., map(), filter(), batch(), take() and also method chaining such operatorsAssumes the reader has very limited experienceCompanion files with all of the source code examples (download from the publisher) Issued also in print. Mode of access: Internet via World Wide Web. In English. Description based on online resource; title from PDF title page (publisher's Web site, viewed 07. Mrz 2024) Python (Computer program language). Programming. COMPUTERS / Programming Languages / Python. bisacsh EPUB 9781683923626 print 9781683923619 https://doi.org/10.1515/9781683923633 https://www.degruyter.com/isbn/9781683923633 Cover https://www.degruyter.com/document/cover/isbn/9781683923633/original |
language |
English |
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eBook |
author |
Campesato, Oswald, Campesato, Oswald, |
spellingShingle |
Campesato, Oswald, Campesato, Oswald, Python for TensorFlow Pocket Primer / Pocket Primer Frontmatter -- Contents -- Preface -- Chapter 1. Introduction to Python -- Chapter 2. Introduction to NumPy -- Chapter 3. Introduction to Pandas -- Chapter 4. Matplotlib, Sklearn, and Seaborn -- Chapter 5. Introduction to TensorFlow -- Chapter 6. TensorFlow Datasets -- Index |
author_facet |
Campesato, Oswald, Campesato, Oswald, |
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VerfasserIn VerfasserIn |
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Campesato, Oswald, |
title |
Python for TensorFlow Pocket Primer / |
title_full |
Python for TensorFlow Pocket Primer / Oswald Campesato. |
title_fullStr |
Python for TensorFlow Pocket Primer / Oswald Campesato. |
title_full_unstemmed |
Python for TensorFlow Pocket Primer / Oswald Campesato. |
title_auth |
Python for TensorFlow Pocket Primer / |
title_alt |
Frontmatter -- Contents -- Preface -- Chapter 1. Introduction to Python -- Chapter 2. Introduction to NumPy -- Chapter 3. Introduction to Pandas -- Chapter 4. Matplotlib, Sklearn, and Seaborn -- Chapter 5. Introduction to TensorFlow -- Chapter 6. TensorFlow Datasets -- Index |
title_new |
Python for TensorFlow Pocket Primer / |
title_sort |
python for tensorflow pocket primer / |
series |
Pocket Primer |
series2 |
Pocket Primer |
publisher |
Mercury Learning and Information, |
publishDate |
2019 |
physical |
1 online resource (218 p.) Issued also in print. |
contents |
Frontmatter -- Contents -- Preface -- Chapter 1. Introduction to Python -- Chapter 2. Introduction to NumPy -- Chapter 3. Introduction to Pandas -- Chapter 4. Matplotlib, Sklearn, and Seaborn -- Chapter 5. Introduction to TensorFlow -- Chapter 6. TensorFlow Datasets -- Index |
isbn |
9781683923633 9781683923626 9781683923619 |
url |
https://doi.org/10.1515/9781683923633 https://www.degruyter.com/isbn/9781683923633 https://www.degruyter.com/document/cover/isbn/9781683923633/original |
illustrated |
Not Illustrated |
dewey-hundreds |
500 - Science |
dewey-tens |
530 - Physics |
dewey-ones |
537 - Electricity & electronics |
dewey-full |
537.2 |
dewey-sort |
3537.2 |
dewey-raw |
537.2 |
dewey-search |
537.2 |
doi_str_mv |
10.1515/9781683923633 |
oclc_num |
1191843296 |
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AT campesatooswald pythonfortensorflowpocketprimer |
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Python for TensorFlow Pocket Primer / |
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