Bleeding Edge Press, 2016. — 316 p. — ISBN: 978-1-939902-35-1 This book is a hands-on introduction to learning algorithms. It is for people who may know a little machine learning (or not) and who may have heard about TensorFlow, but found the documentation too daunting to approach. The learning curve is gentle and you always have some code to illustrate the math step-by-step....
Independently published, 2024. — 110 p. — ASIN: B0CW1DWGH4. Dive into the world of deep learning with "Mastering TensorFlow," your comprehensive guide to harnessing the full potential of TensorFlow for building powerful neural networks. Whether you're a beginner or an experienced practitioner, this book will equip you with the knowledge and skills to tackle real-world...
Packt Publishing, 2021. — 417 p. — ISBN: 9781800208865. Master TensorFlow to create powerful machine learning algorithms, with valuable insights on Keras, Boosted Trees, Tabular Data, Transformers, Reinforcement Learning, and more. Key Features Work with the latest code and examples for TensorFlow 2. Get to grips with the fundamentals including variables, matrices, and data...
Packt Publishing, 2021. — 417 p. — ISBN: 9781800208865. Master TensorFlow to create powerful machine learning algorithms, with valuable insights on Keras, Boosted Trees, Tabular Data, Transformers, Reinforcement Learning, and more. Key Features Work with the latest code and examples for TensorFlow 2. Get to grips with the fundamentals including variables, matrices, and data...
Packt Publishing, 2019. — 184 p. — ISBN: 1789533589. Leverage the power of Tensorflow to Create powerful software agents that can self-learn to perform real-world tasks Key Features Explore efficient Reinforcement Learning algorithms and code them using TensorFlow and Python Train Reinforcement Learning agents for problems, ranging from computer games to autonomous driving....
Packt Publishing, 2017. — 284 p. — ISBN10: 1786466589, ISBN13: 978-1786466587. This book of projects highlights how TensorFlow can be used in different scenarios - this includes projects for training models, machine learning, deep learning, and working with various neural networks. Each project provides exciting and insightful exercises that will teach you how to use TensorFlow...
Manning, 2020. — 350 p. — ISBN: 9781617296178. Deep learning has transformed the fields of computer vision, image processing, and natural language applications. Thanks to TensorFlow.js, now JavaScript developers can build deep learning apps without relying on Python or R. Deep Learning with JavaScript shows developers how they can bring DL technology to the web. Written by the...
Mercury Learning and Information, 2020. — 250 p. 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...
Mercury Learning and Information, 2019. — ISBN: 1683923642 This book introduces TensorFlow to people who have some knowledge of Python. Readers will learn about many “core” TensorFlow APIs, Linear Regression, Logistic Regression, and MultiLayer Perceptrons. This book is meant to provide both a foundation in TensorFlow and a rudimentary understanding of Deep Learning.
Packt Publishing, 2018. — 148 p. — ISBN: 978-1789537291. Key Features Focus on neural network and its essential operations Prepare data for a deep learning model and deploy it as an interactive web application, with Flask and a HTTP API Use Keras, a TensorFlow abstraction library Book Description With this book, you'll learn how to train, evaluate and deploy Tensorflow and...
Packt Publishing, 2021. – 306 p. - ISBN: 1838826785, 9781838826789. Implement real-world DevOps and cloud deployment scenarios using Azure Repos, Azure Pipelines, and other Azure DevOps tools. Key Features Improve your application development life cycle with Azure DevOps in a step-by-step manner. Apply continuous integration and continuous deployment to reduce application...
Packt Publishing, 2017. — 174 p. — ISBN: 978-1-78728-277-3. This book is your guide to exploring the possibilities in the field of deep learning, making use of Google's TensorFlow. You will learn about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data. Dan Van Boxel’s Deep Learning with TensorFlow...
Apress, 2020. — 318 p. — ISBN: 1484262727. Develop and deploy deep learning web apps using the TensorFlow.js library. TensorFlow.js is part of a bigger framework named TensorFlow, which has many tools that supplement it, such as TensorBoard, ml5js, tfjs-vis. This book will cover all these technologies and show they integrate with TensorFlow.js to create intelligent web...
Amazon.com Services LLC, 2021. — 126 p. Introduction to TensorFlow Using Python provides an introduction to using TensorFlow with Python in easy bite-sized pieces that any beginner or novice can understand. Filled with simple working examples, the book aims to introduce the reader to the wonderful world of machine learning. Follow along for an adventure in coding and solving...
India: BPB Publications, 2022. — 421 p. — ISBN: 978-93-91392-222. Mastering TensorFlow 2.x is a must to read and practice if you are interested in building various neural networks with high-level TensorFlow and Keras APIs. The book begins with the basics of TensorFlow and neural network concepts and goes into specific topics like image classification, object detection, time...
Apress, 2020. — 563 p. — ISBN: 1484253485. Build your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts. This book shows you how to build a deep learning pipeline for real-life TensorFlow projects. You'll learn what a pipeline is and how it works so you can build a full application easily and rapidly. Then troubleshoot and overcome...
Manning, 2022. — 680 p. — ISBN: 978-1617298349. TensorFlow in Action teaches you to construct, train, and deploy deep learning models using TensorFlow 2. In this practical tutorial, you’ll build reusable skills hands-on as you create production-ready applications such as a French-to-English translator and a neural network that can write fiction. You’ll appreciate the in-depth...
Apress, 2021. — 334 p. — ISBN: 1484264177. Build machine learning web applications without having to learn a new language. This book will help you develop basic knowledge of machine learning concepts and applications. You’ll learn not only theory, but also dive into code samples and example projects with TensorFlow.js. Using these skills and your already honed skills as a web...
2nd Edition. — Birmingham — Mumbai, Packt Publishing, 2019. — 646 p. — ISBN13: 978-1838823412. Build machine and deep learning systems with the newly released TensorFlow 2 and Keras for the lab, production, and mobile devices Key Features — Introduces and then uses TensorFlow 2 and Keras right from the start — Teaches key machine and deep learning techniques — Understand the...
Packt Publishing, 2017. — 526 p. — ISBN: 1788293592. Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are...
Packt Publishing, 2017. — 536 p. Take the next step in implementing various common and not-so-common neural networks with Tensorflow 1.x Deep neural networks (DNNs) have achieved a lot of success in the field of computer vision, speech recognition, and natural language processing. The entire world is filled with excitement about how deep networks are revolutionizing artificial...
O’Reilly Media, 2017. — 242 p. — ISBN: 978-1491978511. Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy. This practical book provides an end-to-end guide to TensorFlow, the leading open-source software library that helps you build and train neural networks for computer vision,...
Packt Publishing, 2017. — 304 p. — ISBN: 978-1786462961. Tackle common commercial machine learning problems with Google’s TensorFlow 1.x library and build deployable solutions. About This Book Enter the new era of second-generation machine learning with Python with this practical and insightful guide Set up TensorFlow 1.x for actual industrial use, including high-performance...
Packt Publishing, 2017. — 304 p. — ISBN: 978-1786462961. !Only code files! Tackle common commercial machine learning problems with Google’s TensorFlow 1.x library and build deployable solutions. About This Book Enter the new era of second-generation machine learning with Python with this practical and insightful guide Set up TensorFlow 1.x for actual industrial use, including...
Apress, 2020. — 374 p. — ISBN: 1484263723. Machine Learning for Economics and Finance in TensorFlow 2: Deep Learning Models for Research and Industry Work on economic problems and solutions with tools from machine learning. ML has taken time to move into the space of academic economics. This is because empirical work in economics is concentrated on the identification of causal...
Pckt Publishing, 2017. — 552 p. — ISBN: 1788398920. Harness the power of data in your business by building advanced predictive modeling applications with Tensorflow. About This Book A quick guide to gaining hands-on experience with deep learning in different domains such as digit, image & text classification Build your own smart, predictive models with TensorFlow using an...
Packt Publishing, 2018. — 160 p. — ISBN: 1789136911. Learn how to solve real life problems using different methods like logic regression, random forests and SVMs with TensorFlow. Key Features Understand predictive analytics along with its challenges and best practices Embedded with assessments that will help you revise the concepts you have learned in this book Book Description...
Apress, 2021. — 254 p. — ISBN: 1484261674, 9781484261675. Dive into and apply practical machine learning and dataset categorization techniques while learning Tensorflow and deep learning. This book uses convolutional neural networks to do image recognition all in the familiar and easy to work with Swift language. It begins with a basic machine learning overview and then ramps...
O’Reilly Media, Inc., 2021. — 342 p. — ISBN: 978-1-492-09079-3. 2021-05-07: First Release Given the demand for AI and the ubiquity of JavaScript, TensorFlow.js was inevitable. With this Google framework, seasoned AI veterans and web developers alike can help propel the future of AI-driven websites. In this guide, author Gant Laborde--Google Developer Expert in machine...
Apress, 2022 — 785 p. — ISBN: 148427914X. Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras. The materials used in this book are based on years of successful online education experience and feedback from thousands of online learners.
Apress, 2018. — 227 p. — ISBN: 1484235150. Build deep learning applications, such as computer vision, speech recognition, and chatbots, using frameworks such as TensorFlow and Keras. This book helps you to ramp up your practical know-how in a short period of time and focuses you on the domain, models, and algorithms required for deep learning applications. Deep Learning with...
Packt, 2022. — 344 p. — ISBN: 978-1-801-81497-3. This book explores TinyML, a fast-growing field at the unique intersection of machine learning and embedded systems to make AI ubiquitous with extremely low-powered devices such as microcontrollers. The TinyML Cookbook starts with a practical introduction to this multidisciplinary field to get you up to speed with some of the...
Packt Publishing, 2021. — 542 p. — ISBN 9781838829131. Get well versed with state-of-the-art techniques to tailor training processes and boost the performance of computer vision models using machine learning and deep learning techniques Key Features Develop, train, and use deep learning algorithms for computer vision tasks using TensorFlow 2.x Discover practical recipes to...
Packt Publishing, 2018. — 320 p. — ISBN: 1788398068. Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios. Key Features Build efficient deep learning pipelines using the popular Tensorflow framework Train neural networks such as ConvNets, generative models, and LSTMs Includes projects related to Computer Vision, stock...
Packt Publishing, 2018. — 320 p. — ISBN: 1788398068. Leverage the power of Tensorflow to design deep learning systems for a variety of real-world scenarios. Key Features Build efficient deep learning pipelines using the popular Tensorflow framework Train neural networks such as ConvNets, generative models, and LSTMs Includes projects related to Computer Vision, stock...
2nd Edition. — Manning Publications, 2020. — 454 p. — ISBN: 9781617297717. Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives readers a solid foundation in machine-learning concepts and the TensorFlow library. Updated with new code, new projects, and new chapters, Machine Learning with TensorFlow, Second Edition gives...
2nd Edition. — Manning Publications, 2020. — 471 p. — ISBN: 9781617297717. This fully revised second edition of Machine Learning with TensorFlow teaches you the foundational concepts of machine learning, and how to utilize the TensorFlow library to rapidly build powerful ML models. You'll learn the basics of regression, classification, and clustering algorithms, applying them...
2nd edition. — Packt, 2018. — 422 p. TensorFlow Machine Learning Cookbook: Over 60 recipes to build intelligent machine learning systems with the power of Python, 2nd Edition Skip the theory and get the most out of Tensorflow to build production-ready machine learning models TensorFlow is an open-source software library for Machine Intelligence. The independent recipes in this...
Packt Publishing, 2017. — 370 p. — ISBN: 978-1-78646-216-9. — True PDF. TensorFlow is an open-source software library for Machine Intelligence. The independent recipes in this book will teach you how to use TensorFlow for complex data computations and will let you dig deeper and gain more insights into your data than ever before. You'll work through recipes on training models,...
2nd Edition. — Apress, 2022. — 397 p. — ISBN: 1484280199. Understand how neural networks work and learn how to implement them using TensorFlow 2.0 and Keras. This new edition focuses on the fundamental concepts and at the same time on practical aspects of implementing neural networks and deep learning for your research projects. This book is designed so that you can focus on...
Packt Publishing, 2021 — 601 p. — ISBN: 1800205252. Get started with TensorFlow fundamentals to build and train deep learning models with real-world data, practical exercises, and challenging activities Getting to grips with tensors, deep learning, and neural networks can be intimidating and confusing for anyone, no matter their experience level. The breadth of information out...
Packt Publishing, 2021. — 472 p. — ISBN: 183898254X, 9781838982546. Discover recipes for developing AI applications to solve a variety of real-world business problems using reinforcement learning Key Features Develop and deploy deep reinforcement learning-based solutions to production pipelines, products, and services Explore popular reinforcement learning algorithms such as...
Apress, 2021. — 290 p. — ISBN: 9781484266489. Use TensorFlow 2.x with Google's Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab’s default install of the most current TensorFlow 2.x along with Colab’s easy access to on-demand GPU...
Apress, 2021. — 388 p. — ISBN: 1484273400. Use TensorFlow 2.x in the Google Colab ecosystem to create state-of-the-art deep learning models guided by hands-on examples. The Colab ecosystem provides a free cloud service with easy access to on-demand GPU (and TPU) hardware acceleration for fast execution of the models you learn to build. This book teaches you, state-of-the-art...
GitforGits, 2023. — 212 p. — ISBN-13: 978-8119177325. Designed with both beginners and professionals in mind, the book is meticulously structured to cover a broad spectrum of concepts, applications, and hands-on practices that form the core of the TensorFlow Developer Certificate exam. Starting with foundational concepts, the book guides you through the fundamental aspects of...
Apress, 2018. — 398 p. Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFlow provides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful...
Packt, 2019. — 372 p. — ISBN: 9781788830645. A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more. Key Features Discover how to build, train, and serve your own deep neural networks with TensorFlow 2 and Keras Apply modern solutions to a wide range of applications such as object detection...
Springer, 2021. — 190 p. — (EAI/Springer Innovations in Communication and Computing). — ISBN: 978-3030570767. This sensible book offers an finish-to-finish information to TensorFlow, the main open supply software program library that helps you construct and practice neural networks for deep studying, Natural Language Processing (NLP), speech recognition, and basic predictive...
Springer, 2021. — 190 p. — (EAI/Springer Innovations in Communication and Computing). — ISBN: 978-3-030-57076-7. This practical book provides an end-to-end guide to TensorFlow, the leading open-source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics. The...
Independently published, 2018. — 364 p. — ISBN: 1720092257. Tensorflow is the most popular Deep Learning Library out there. It has fantastic graph computations feature which helps data scientist to visualize his designed neural network using TensorBoard. This Machine learning library supports both Convolution as well as Recurrent Neural network. It supports parallel processing...
Wiley, 2018. — 360 p. — (For Dummies). — ISBN: 1119466210. Become a machine learning pro! Google TensorFlow has become the darling of financial firms and research organizations, but the technology can be intimidating and the learning curve is steep. Luckily, TensorFlow For Dummies is here to offer you a friendly, easy–to–follow book on the subject. Inside, you ll find out how...
Manning Publishing, 2017. — 251 p. — ISBN: 1617293873. Machine Learning with TensorFlow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding TensorFlow with Python. You'll learn the basics by working with classic prediction, classification, and clustering algorithms. Then, you'll move on to the money chapters: exploration of...
Manning Publishing, 2017. — 251 p. — ISBN: 1617293873. true PDF MEAP edition Being able to make near-real-time decisions is becoming increasingly crucial. To succeed, we need machine learning systems that can turn massive amounts of data into valuable insights. But when you're just starting out in the data science field, how do you get started creating machine learning...
Apress, 2020. - 312 p. - ISBN: 9781484259665 Create, execute, modify, and share machine learning applications with Python and TensorFlow 2.0 in the Jupyter Notebook environment. This book breaks down any barriers to programming machine learning applications through the use of Jupyter Notebook instead of a text editor or a regular IDE. You’ll start by learning how to use Jupyter...
Apress, 2020. — 177 p. Learn how to use TensorFlow 2.0 to build machine learning and deep learning models with complete examples. The book begins with introducing TensorFlow 2.0 framework and the major changes from its last release. Next, it focuses on building Supervised Machine Learning models using TensorFlow 2.0. It also demonstrates how to build models using customer...
Independently published, 2021. — 500 p. — ASIN B08YZ1RXB2. While TensorFlow is an incredibly important machine and deep learning library, we also give you an introduction to three others – NumPy, Pandas, and Scikit Learn. I have produced a hands-on guide, with plenty of code examples for you to follow along with Here’s what you will learn: What deep learning is The difference...
O’Reilly Media, Inc., 2021. — 255 p. — ISBN: 978-1-492-08918-6. 2021-07-19: First Release 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...
O’Reilly, 2020. — 576 p. — ISBN: 978-1-492-05204-3. Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size — small enough to work on the digital signal processor in an Android phone. With this practical book, you’ll learn about TensorFlow Lite for Microcontrollers, a miniscule...
O’Reilly, 2020. — 504 p. — ISBN: 978-1-492-05204-3. Neural networks are getting smaller. Much smaller. The OK Google team, for example, has run machine learning models that are just 14 kilobytes in size — small enough to work on the digital signal processor in an Android phone. With this practical book, you’ll learn about TensorFlow Lite for Microcontrollers, a miniscule...
Apress, 2020. -314 p. - ISBN: 9781484265123 Implement deep learning applications using TensorFlow while learning the “why” through in-depth conceptual explanations. You’ll start by learning what deep learning offers over other machine learning models. Then familiarize yourself with several technologies used to create deep learning models. While some of these technologies are...
2nd ed. — Packt Publishing, 2018. — 484 p. — ISBN: 978-1-78883-110-9. Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of TensorFlow v1.7. Deep learning is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, which are at the core of deep learning, are being...
Packt Publishing, 2017. — 320 p. — ISBN: 978-1-78646-978-6. Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide. Deep learning is the step that comes after machine learning, and has more advanced implementations. Machine learning is not just for academics anymore, but is...
Packt Publishing, 2016. — 180 p. — ISBN: 978-1-78646-857-4. Get up and running with the latest numerical computing library by Google and dive deeper into your data! Google's TensorFlow engine, after much fanfare, has evolved in to a robust, user-friendly, and customizable, application-grade software library of machine learning (ML) code for numerical computation and neural...
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