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Android pocket primer
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ISBN: 1683920899 Year: 2017 Publisher: Dulles, Virginia ; Boston, [Massachusetts] ; New Delhi, [India] : Mercury Learning and Information,

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As part of the best selling Pocket Primer series, this book provides an overview of the major aspects and the source code to use the latest versions of Android. It has coverage of the fundamental aspects of Android that are illustrated via code samples for versions 4.x through 7.x and features the Google Pixel phone. This Pocket Primer is primarily for self-directed learners who want to learn Android programming and it serves as a starting point for deeper exploration of its numerous applications. Companion disc (also available for downloading from the publisher) with source code, images, and appendices.Features:*Contains latest material on Android VR, graphics/animation, apps, and features the new Google Pixel phone*Includes companion files with all of the source code, appendices, and images from the book *Provides coverage of the fundamental aspects of Android that are illustrated via code samples for versions 4.x through 7.xOn the Companion Files:* Source code samples* All images from the text (including 4-color)* Appendices (see Table of Contents)


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Angular and deep learning : pocket primer
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ISBN: 1683924711 Year: 2021 Publisher: Dulles, Virginia : Mercury Learning and Information,

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Angular 4 Pocket Primer
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ISBN: 1683920368 Year: 2018 Publisher: Dulles, VA : M ercury Learning and Information LLC,

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Regular expressions
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ISBN: 1683923111 Year: 2018 Publisher: Bloomfield : Mercury Learning & Information,

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Introduces readers to regular expressions in several technologies. The book shows 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.


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TensorFlow 2.0 : pocket primer
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ISBN: 1683924614 Year: 2020 Publisher: Dulles, Virginia ; Boston, Massachusetts ; New Delhi : Mercury Learning and Information,

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As part of thebest-selling Pocket Primerseries, thisbook is designed to introducebeginners to basic machine learning algorithms using TensorFlow 2. It isintended to be a fast-paced introduction to various "core" features ofTensorFlow, with code samples that cover machine learning and TensorFlowbasics. A comprehensive appendix contains someKeras-based code samples and the underpinnings of MLPs, CNNs, RNNs, and LSTMs. The material inthe chapters illustrates how to solve a variety of tasks after which you can dofurther reading to deepen your knowledge. Companion files with all of the codesamples are available for downloading from the publisher by emailing proof of purchase to info@merclearning.com.Features:Uses Python for codesamplesCovers TensorFlow 2 APIsand DatasetsIncludes a comprehensiveappendix that covers Keras and advanced topics such as NLPs, MLPs, RNNs, LSTMsFeatures the companion files with all of thesource code examples and figures (download fromthe publisher)

Keywords

TensorFlow.


Book
Data Science Fundamentals : Pocket Primer
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ISBN: 1683927311 9781683927310 1683927338 9781683927334 Year: 2021 Publisher: Dulles, Virginia : Mercury Learning and Information,

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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.


Book
Artificial intelligence, machine learning, and deep learning
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ISBN: 1683924657 Year: 2020 Publisher: Dulles, Virginia ; Boston, Massachusetts ; New Delhi : Mercury Learning and Information,

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Python 3 for machine learning
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ISBN: 1683924932 Year: 2020 Publisher: Dulles, Virginia ; Boston, Massachusetts ; New Delhi : Mercury Learning and Information,

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This book is designed to provide the reader with basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter introduces the fundamental concepts of machine learning. The sixth chapter is devoted to machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on NLP and RL. Keras-based code samples are included to supplement the theoretical discussion. The book also contains separate appendices for regular expressions, Keras, and TensorFlow 2. -- Provided by publisher.


Book
Sanierungskredite unter dem Regelwerk des Insolvenzplanverfahrens : Risiken der Banken bei Darlehen an Unternehmen nach Ende ihrer Planinsolvenz
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ISBN: 3658250135 Year: 2019 Publisher: Wiesbaden : Springer Fachmedien Wiesbaden : Imprint: Springer Gabler,

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Das Insolvenzplanverfahren als Sanierungsinstrument gewinnt mit zunehmender Globalisierung immer mehr an Bedeutung. Gerade in der kritischen Phase nach Aufhebung der Insolvenz zum Übergang in die Planüberwachung ist der Sanierungserfolg der Gesellschaft jedoch abhängig von der Zuführung neuer Liquidität. Die vorliegende Untersuchung arbeitet in diesem Zusammenhang den Begriff des Sanierungskredits sowie die speziellen Risiken für Banken heraus und zeigt eine Herangehensweise zur Minimierung ihrer Haftungsgefahren. Hierbei hinterfragt die Autorin insbesondere, ob auf ein zeit- und kostenintensives Sanierungsgutachten zum Zeitpunkt nach Aufhebung des Insolvenzplanverfahrens ausnahmsweise verzichtet werden kann. Inhalt Rechtliche Risiken des Kreditgebers bei Sanierungskrediten Konzept zur Minimierung der Haftungsrisiken Reichweite der gerichtlichen Entscheidungskompetenz im Insolvenzplanverfahren Entbehrlichkeit des Sanierungsgutachtens nach Aufhebung des Insolvenzverfahrens? Die Zielgruppen Dozenten und Studenten der Rechtswissenschaften mit den Schwerpunkten Wirtschafts-, Insolvenz- und Bankrecht Fach- und Führungskräfte in den Bereichen Insolvenzrecht, Banking/Kreditgeschäfte und Unternehmensbewertung Die Autorin Dr. Antje Oswald ist Zivilrichterin am Amtsgericht in Frankfurt am Main und war zuvor als Associate in einer internationalen Wirtschaftskanzlei in den Bereichen Banking, Restrukturierung und Insolvenzrecht tätig. Ihre Promotion erfolgte auf den Gebieten des Gesellschafts- und Versicherungsrechts.


Book
Dealing with data : pocket primer
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ISBN: 1523147407 1683928180 1683928199 9781523147403 9781683928188 9781683928195 Year: 2022 Publisher: Dulles, VA : Mercury Learning and Information,

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As part of the best-selling Pocket Primer series, this book is designed to introduce the reader to the basic concepts of managing data using a variety of computer languages and applications. It is intended to be a fast-paced introduction to some basic features of data management and covers statistical concepts, data-related techniques, features of Pandas, RDBMS, SQL, NLP topics, Matplotlib, and data visualization. Companion files with source code and color figures are available. FEATURES: Covers Pandas, RDBMS, NLP, data cleaning, SQL, and data visualization. Introduces probability and statistical concepts. Features numerous code samples throughout. Includes companion files with source code and figures.

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