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Tensorflow Pocket Primer
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Book Synopsis TensorFlow Pocket Primer by : Oswald Campesato
Download or read book TensorFlow Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2019-05-09 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to TensorFlow 1.x fundamentals for basic machine learning algorithms in TensorFlow. It is intended to be a fast-paced introduction to various “core” features of TensorFlow, with code samples that cover deep learning and TensorFlow basics. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by writing to [email protected]. Features: Uses Python for code samples Covers TensorFlow APIs and Datasets Assumes the reader has very limited experience Companion files with all of the source code examples (download from the publisher)
Book Synopsis TensorFlow 2 Pocket Primer by : Oswald Campesato
Download or read book TensorFlow 2 Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2019-08-27 with total page 229 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to introduce beginners to basic machine learning algorithms using TensorFlow 2. It is intended to be a fast-paced introduction to various “core” features of TensorFlow, with code samples that cover machine learning and TensorFlow basics. A comprehensive appendix contains some Keras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material in the chapters illustrates how to solve a variety of tasks after which you can do further reading to deepen your knowledge. Companion files with all of the code samples are available for downloading from the publisher by emailing proof of purchase to [email protected]. Features: Uses Python for code samples Covers TensorFlow 2 APIs and Datasets Includes a comprehensive appendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMs Features the companion files with all of the source code examples and figures (download from the publisher)
Book Synopsis Python for TensorFlow Pocket Primer by : Oswald Campesato
Download or read book Python for TensorFlow Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2019-05-09 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 [email protected]. 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 Companion files with all of the source code examples (download from the publisher)
Book Synopsis Deep Learning Pocket Primer by : Oswald Campesato
Download or read book Deep Learning Pocket Primer written by Oswald Campesato and published by . This book was released on 2019-04-30 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Angular and Deep Learning Pocket Primer by : Oswald Campesato
Download or read book Angular and Deep Learning Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2020-10-13 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic deep learning concepts and incorporate that knowledge into Angular 10 applications. It is intended to be a fast-paced introduction to some basic features of deep learning and an overview of several popular deep learning classifiers. The book includes code samples and numerous figures and covers topics such as Angular 10 functionality, basic deep learning concepts, classification algorithms, TensorFlow, and Keras. Companion files with code and color figures are included. FEATURES: Introduces basic deep learning concepts and Angular 10 applications Covers MLPs (MultiLayer Perceptrons) and CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), LSTMs (Long Short-Term Memory), GRUs (Gated Recurrent Units), autoencoders, and GANs (Generative Adversarial Networks) Introduces TensorFlow 2 and Keras Includes companion files with source code and 4-color figures. The companion files are also available online by emailing the publisher with proof of purchase at [email protected].
Download or read book Python written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2012-12-15 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the new Pocket Primer series, this book provides an overview of the major aspects and the source code to use Python 2. It covers the latest Python developments, built-in functions and custom classes, data visualization, graphics, databases, and more. It includes a companion disc with appendices, source code, and figures. This Pocket Primer is primarily for self-directed learners who want to learn Python 2 and it serves as a starting point for deeper exploration of Python programming. Features: +Includes a companion disc with appendices, source code, and figures +Contains material devoted to Raspberry Pi, Roomba, JSON, and Jython +Includes latest Python 2 developments, built-in functions and custom classes, data visualization, graphics, databases, and more +Provides a solid introduction to Python 2 via complete code samples On the CD-ROM: +Appendices (HTML5 and JavaScript Toolkits, Jython, SPA) +Source code samples +All images from the text (including 4-color) +Solutions to Odd-Numbered Exercises
Book Synopsis Angular and Machine Learning Pocket Primer by : Oswald Campesato
Download or read book Angular and Machine Learning Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2020-03-27 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to basic machine learning concepts and incorporate that knowledge into Angular applications. The book is intended to be a fast-paced introduction to some basic features of machine learning and an overview of several popular machine learning classifiers. It includes code samples and numerous figures and covers topics such as Angular functionality, basic machine learning concepts, classification algorithms, TensorFlow and Keras. The files with code and color figures are on the companion disc with the book or available from the publisher. Features: Introduces the basic machine learning concepts and Angular applications Includes source code and full color figures
Book Synopsis TensorFlow 2 Pocket Reference by : KC Tung
Download or read book TensorFlow 2 Pocket Reference written by KC Tung and published by "O'Reilly Media, Inc.". This book was released on 2021-07-19 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself. When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the training process? How do you leverage a pretrained model using transfer learning? How do you perform hyperparameter tuning? Pick up this pocket reference and reduce the time you spend searching through options for your TensorFlow use cases. Understand best practices in TensorFlow model patterns and ML workflows Use code snippets as templates in building TensorFlow models and workflows Save development time by integrating prebuilt models in TensorFlow Hub Make informed design choices about data ingestion, training paradigms, model saving, and inferencing Address common scenarios such as model design style, data ingestion workflow, model training, and tuning
Book Synopsis R for Deep Learning Pocket Primer by : OSWALD. CAMPESATO
Download or read book R for Deep Learning Pocket Primer written by OSWALD. CAMPESATO and published by . This book was released on 2023-12-14 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Natural Language Processing using R Pocket Primer by : Oswald Campesato
Download or read book Natural Language Processing using R Pocket Primer written by Oswald Campesato and published by Stylus Publishing, LLC. This book was released on 2022-01-05 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is for developers who are looking for an overview of basic concepts in Natural Language Processing using R. It casts a wide net of techniques to help developers who have a range of technical backgrounds. Numerous code samples and listings are included to support myriad topics. The final chapter presents the Transformer Architecture, BERT-based models, and the GPT family of models, all of which were developed during the past three years. Companion files with source code and figures are included and available for downloading by emailing the publisher at [email protected] with proof of purchase. FEATURES: Covers extensive topics related to natural language processing using R Features companion files with source code and figures from the book
Download or read book SVG written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2016-09-15 with total page 319 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the Pocket Primer series, this book provides an overview of the major aspects and the source code to use SVG. This Pocket Primer is primarily for self-directed learners who want to learn SVG and it serves as a starting point for deeper exploration of its programming. Features: • Includes companion files with all of the source code and images from the book • Contains material devoted to SVG gradients and filters, graphics, animation, etc., use with CSS3, D3, Angular2, and covers SVG application programming interfaces and other toolkits • Provides a solid introduction to SVG via complete code samples and images Companion Files: • Source code samples • All images from the text (including 4-color)
Download or read book CSS3 written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2016-09-15 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the Pocket Primer series, this book provides an overview of the major aspects and the source code to use CSS3. This Pocket Primer is primarily for self-directed learners who want to learn CSS3 and it serves as a starting point for deeper exploration of its programming. Features: •Includes companion files with appendices, source code, and figures •Contains material devoted to CSS3 on mobile devices, use with SVG and HTML5 Canvas, JavaScript, and covers CSS3 application programming interfaces and other toolkits •Provides a solid introduction to CSS3 via complete code samples and images Companion Files: •Source code samples •Appendices Appendix A - jQuery Appendix B - CSS Frameworks & Toolkits • All images from the text (including 4-color) eBook Customers: Companion files are available for downloading with order number/proof of purchase by writing to the publisher at [email protected].
Book Synopsis Regular Expressions by : Oswald Campesato
Download or read book Regular Expressions written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2018-06-04 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the bestselling Pocket Primer series, the goal of this book is to introduce readers to regular expressions in several technologies. It is intended for data scientists, data analysts, and others who want to understand regular expressions to perform various tasks. You will acquire an understanding of how to create an assortment of regular expressions, such as filtering data for strings containing uppercase or lowercase letters; matching integers, decimals, hexadecimal, and scientific numbers; and context-dependent pattern matching expressions. It includes REs with Python, R, bash, Perl, Java, and more. Companion files with source code are available for downloading from the publisher. Features: • Uses REs with Python, R, bash, Java, and more • Packed with realistic examples and numerous commands • Assumes the reader has no prior experience, but the topic is covered comprehensively enough to teach a pro some new tricks • Includes companion files with all of the source code examples (download from the publisher) ON THE COMPANION FILES (available from the publisher for downloading) • Source code samples
Book Synopsis Python Data Structures Pocket Primer by : Oswald Campesato
Download or read book Python Data Structures Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2022-12-06 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to present the fundamentals of data structures using Python. Data structures provide a means to manage huge amounts of information such as large databases and the ability to use search and sort algorithms effectively. It is intended to be a fast-paced introduction to the core concepts of Python and data structures, illustrated with numerous code samples. Companion files with source code are available for downloading. FEATURES: Begins with an introduction to Python, and covers recursion, strings, search and sort, linked lists, stacks, and more Features numerous code samples throughout Includes companion files with source code available for downloading.
Book Synopsis Artificial Intelligence, Machine Learning, and Deep Learning by : Oswald Campesato
Download or read book Artificial Intelligence, Machine Learning, and Deep Learning written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2020-01-23 with total page 306 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book begins with an introduction to AI, followed by machine learning, deep learning, NLP, and reinforcement learning. Readers will learn about machine learning classifiers such as logistic regression, k-NN, decision trees, random forests, and SVMs. Next, the book covers deep learning architectures such as CNNs, RNNs, LSTMs, and auto encoders. Keras-based code samples are included to supplement the theoretical discussion. In addition, this book contains appendices for Keras, TensorFlow 2, and Pandas. Features: Covers an introduction to programming concepts related to AI, machine learning, and deep learning Includes material on Keras, TensorFlow2 and Pandas
Book Synopsis TensorFlow 2 Pocket Reference by : K. C. Tung
Download or read book TensorFlow 2 Pocket Reference written by K. C. Tung and published by O'Reilly Media. This book was released on 2021-11-16 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: This easy-to-use reference for TensorFlow 2 design patterns in Python will help you make informed decisions for various use cases. Author KC Tung addresses common topics and tasks in enterprise data science and machine learning practices rather than focusing on TensorFlow itself. When and why would you feed training data as using NumPy or a streaming dataset? How would you set up cross-validations in the training process? How do you leverage a pretrained model using transfer learning? How do you perform hyperparameter tuning? Pick up this pocket reference and reduce the time you spend searching through options for your TensorFlow use cases. Understand best practices in TensorFlow model patterns and ML workflows Use code snippets as templates in building TensorFlow models and workflows Save development time by integrating prebuilt models in TensorFlow Hub Make informed design choices about data ingestion, training paradigms, model saving, and inferencing Address common scenarios such as model design style, data ingestion workflow, model training, and tuning
Book Synopsis Data Science Fundamentals Pocket Primer by : Oswald Campesato
Download or read book Data Science Fundamentals Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2021-05-12 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of data science using Python 3 and other computer applications. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, linear algebra, and regular expressions. The book includes numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available. FEATURES: Includes a concise introduction to Python 3 and linear algebra Provides a thorough introduction to data visualization and regular expressions Covers NumPy, Pandas, R, and SQL Introduces probability and statistical concepts Features numerous code samples throughout Companion files with source code and figures
