Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Python For Tensorflow Pocket Primer
Download Python For Tensorflow Pocket Primer full books in PDF, epub, and Kindle. Read online Python For Tensorflow Pocket Primer ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
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 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)
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 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 Python Tools for Data Scientists Pocket Primer by : Oswald Campesato
Download or read book Python Tools for Data Scientists Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2022-10-21 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: As part of the best-selling Pocket Primer series, this book is designed to provide a thorough introduction to numerous Python tools for data scientists. The book covers features of NumPy and Pandas, how to write regular expressions, and how to perform data cleaning tasks. It includes separate chapters on data visualization and working with Sklearn and SciPy. Companion files with source code are available. FEATURES: Introduces Python, NumPy, Sklearn, SciPy, and awk Covers data cleaning tasks and data visualization Features numerous code samples throughout Includes companion files with source code
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 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 Python 3 and Data Analytics Pocket Primer by : Oswald Campesato
Download or read book Python 3 and Data Analytics Pocket Primer written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2021-03-19 with total page 390 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 analytics using Python 3. It is intended to be a fast-paced introduction to some basic features of data analytics and also covers statistics, data visualization, and data cleaning. The book includes numerous code samples using NumPy, Pandas, Matplotlib, Seaborn, and features an appendix on regular expressions. Companion files with source code and color figures are available online by emailing the publisher with proof of purchase at [email protected]. FEATURES: Includes a concise introduction to Python 3 Provides a thorough introduction to data and data cleaning Covers NumPy and Pandas Introduces statistical concepts and data visualization (Matplotlib/Seaborn) Features an appendix on regular expressions Includes companion files with source code and figures
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].
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
Download or read book Android written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2017-04-13 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.x On the Companion Files: • Source code samples • All images from the text (including 4-color) • Appendices (see Table of Contents)
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
Book Synopsis Python 3 for Machine Learning by : Oswald Campesato
Download or read book Python 3 for Machine Learning written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2020-02-07 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Features: Provides the reader with basic Python 3 programming concepts related to machine learning Includes separate appendices for regular expressions, Keras, and TensorFlow 2
Book Synopsis Python for Programmers by : Oswald Campesato
Download or read book Python for Programmers written by Oswald Campesato and published by Mercury Learning and Information. This book was released on 2022-08-23 with total page 431 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is intended primarily for developers who have little or no experience with Python or Pandas. It contains a fast-paced introduction to Python and Python-based solutions to various tasks. Chapter 1 provides a quick tour of basic Python 3, followed by a chapter that shows how to work with loops and conditional logic in Python. Chapter 3 discusses data structures in Python, followed by a chapter that features code samples for tasks with strings and arrays in Python. Chapter 5 contains concepts in object-oriented programming, along with code samples that illustrate how they are implemented in Python. Chapter 6 introduces recursion and some fundamental topics in combinatorics. Finally, the appendix provides an introduction to Pandas. Companion files with code and figures are available for downloading from the publisher. Features: Provides the reader with basic Python 3 and Pandas programming concepts Companion files with code and figures
Download or read book Hands-on TinyML written by Rohan Banerjee and published by BPB Publications. This book was released on 2023-06-09 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to deploy complex machine learning models on single board computers, mobile phones, and microcontrollers KEY FEATURES ● Gain a comprehensive understanding of TinyML's core concepts. ● Learn how to design your own TinyML applications from the ground up. ● Explore cutting-edge models, hardware, and software platforms for developing TinyML. DESCRIPTION TinyML is an innovative technology that empowers small and resource-constrained edge devices with the capabilities of machine learning. If you're interested in deploying machine learning models directly on microcontrollers, single board computers, or mobile phones without relying on continuous cloud connectivity, this book is an ideal resource for you. The book begins with a refresher on Python, covering essential concepts and popular libraries like NumPy and Pandas. It then delves into the fundamentals of neural networks and explores the practical implementation of deep learning using TensorFlow and Keras. Furthermore, the book provides an in-depth overview of TensorFlow Lite, a specialized framework for optimizing and deploying models on edge devices. It also discusses various model optimization techniques that reduce the model size without compromising performance. As the book progresses, it offers a step-by-step guidance on creating deep learning models for object detection and face recognition specifically tailored for the Raspberry Pi. You will also be introduced to the intricacies of deploying TensorFlow Lite applications on real-world edge devices. Lastly, the book explores the exciting possibilities of using TensorFlow Lite on microcontroller units (MCUs), opening up new opportunities for deploying machine learning models on resource-constrained devices. Overall, this book serves as a valuable resource for anyone interested in harnessing the power of machine learning on edge devices. WHAT YOU WILL LEARN ● Explore different hardware and software platforms for designing TinyML. ● Create a deep learning model for object detection using the MobileNet architecture. ● Optimize large neural network models with the TensorFlow Model Optimization Toolkit. ● Explore the capabilities of TensorFlow Lite on microcontrollers. ● Build a face recognition system on a Raspberry Pi. ● Build a keyword detection system on an Arduino Nano. WHO THIS BOOK IS FOR This book is designed for undergraduate and postgraduate students in the fields of Computer Science, Artificial Intelligence, Electronics, and Electrical Engineering, including MSc and MCA programs. It is also a valuable reference for young professionals who have recently entered the industry and wish to enhance their skills. TABLE OF CONTENTS 1. Introduction to TinyML and its Applications 2. Crash Course on Python and TensorFlow Basics 3. Gearing with Deep Learning 4. Experiencing TensorFlow 5. Model Optimization Using TensorFlow 6. Deploying My First TinyML Application 7. Deep Dive into Application Deployment 8. TensorFlow Lite for Microcontrollers 9. Keyword Spotting on Microcontrollers 10. Conclusion and Further Reading Appendix
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
