Deep Learning with TensorFlow 2ed pdf+epub

Every week, we follow news of applications and the shocking results obtained from them, thanks to the artificial intelligence algorithms applied in different fields. What we are witnessing is one of the biggest accelerations in the entire history of this sector, and the main suspect behind these important developments is called deep learning. Deep learning comprises a vast set of algorithms that are based on the concept of neural networks and expand to contain a huge number of nodes that are disseminated at several levels of depth. Though the concept of neural networks, the socalled Artificial Neural Network (ANN), dates back to the late 1940s, initially, they were difficult to be used because of the need for huge computational power resources and the lack of data required to train the algorithms. Presently, the ability to use graphics processors (GPUs) in parallel to perform intensive calculation operations has completely opened the way to the use of deep learning. In this context, we propose the second edition of this book, with expanded and revised contents that introduce the core concepts of deep learning, using the last version of TensorFlow.

20190827
 10.55MB
Deep learning with tensorflow 2017.4.pdf
20170501Deep learning with tensorflow 2017.4.pdf
 13.27MB
Deep Learning with TensorFlow第二版pdf
20180524Apply deep machine intelligence and GPU computing with TensorFlow v1.7 Access public datasets and use TensorFlow to load, process, and transform the data Discover how to use the highlevel TensorFlow API to build more powerful applications Use deep learning for scalable object detection and mobile computing Train machines quickly to learn from data by exploring reinforcement learning techniques Explore active areas of deep learning research and applications
 10.96MB
Deep Learning with TensorFlow Second Edition（2018年3月出版PDF第2版无水印英文原版带书签）
20180508Deep Learning with TensorFlow Second Edition（2018年3月出版PDF第2版无水印英文原版带书签），研究深度学习和TensorFlow的了解一下。
 4.95MB
Deep Learning with TensorFlow: Explore neural networks with Python
20180729Delve into neural networks, implement deep learning algorithms, and explore layers of data abstraction with the help of this comprehensive TensorFlow guide About This BookLearn how to implement advanced techniques in deep learning with Google’s brainchild, TensorFlowExplore deep neural networks and layers of data abstraction with the help of this comprehensive guideRealworld contextualization through some deep learning problems concerning research and application Who This Book Is For The book is intended for a general audience of people interested in machine learning and machine intelligence. A rudimentary level of programming in one language is assumed, as is a basic familiarity with computer science techniques and technologies, including a basic awareness of computer hardware and algorithms. Some competence in mathematics is needed to the level of elementary linear algebra and calculus. What You Will LearnLearn about machine learning landscapes along with the historical development and progress of deep learningLearn about deep machine intelligence and GPU computing with the latest TensorFlow 1.xAccess public datasets and utilize them using TensorFlow to load, process, and transform dataUse TensorFlow on realworld datasets, including images, text, and moreLearn how to evaluate the performance of your deep learning modelsUsing deep learning for scalable object detection and mobile computingTrain machines quickly to learn from data by exploring reinforcement learning techniquesExplore active areas of deep learning research and applicationsIn Detail 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 becoming a mainstream practice through wide adoption, and deep learning has taken the front seat. As a data scientist, if you want to explore data abstraction layers, this book will be your guide. This book shows how this can be exploited in the real world with complex raw data using TensorFlow 1.x. Throughout the book, you’ll learn how to implement deep learning algorithms for machine learning systems and integrate them into your product offerings, including search, image recognition, and language processing. Additionally, you’ll learn how to analyze and improve the performance of deep learning models. This can be done by comparing algorithms against benchmarks, along with machine intelligence, to learn from the information and determine ideal behaviors within a specific context. After finishing the book, you will be familiar with machine learning techniques, in particular the use of TensorFlow for deep learning, and will be ready to apply your knowledge to research or commercial projects. Style and approach This stepbystep guide will explore common, and not so common, deep neural networks and show how these can be exploited in the real world with complex raw data. With the help of practical examples, you will learn how to implement different types of neural nets to build smart applications related to text, speech, and image data processing.
 12.72MB
Pro Deep Learning with TensorFlow.
20171212Pro Deep Learning with TensorFlow is a practical and mathematical guide to deep learning using TensorFlow. Deep learning is a branch of machine learning where you model the world in terms of a hierarchy of concepts. This pattern of learning is similar to the way a human brain learns, and it allows computers to model complex concepts that often go unnoticed in other traditional methods of modeling. Hence, in the modern computing paradigm, deep learning plays a vital role in modeling complex realworld problems, especially by leveraging the massive amount of unstructured data available today
 15.73MB
Pro Deep Learning with TensorFlow 原版PDF
20180201Pro Deep Learning with TensorFlow 原版PDF，出版商正式版，不是扫描版，不是epub转换版
 12.20MB
Pro Deep Learning with TensorFlow
20171214Pro Deep Learning with TensorFlow is a practical and mathematical guide to deep learning using TensorFlow. Deep learning is a branch of machine learning where you model the world in terms of a hierarchy of concepts. This pattern of learning is similar to the way a human brain learns, and it allows computers to model complex concepts that often go unnoticed in other traditional methods of modeling. Hence, in the modern computing paradigm, deep learning plays a vital role in modeling complex realworld problems, especially by leveraging the massive amount of unstructured data available today. Because of the complexities involved in a deeplearning model, many times it is treated as a black box by people using it. However, to derive the maximum benefit from this branch of machine learning, one needs to uncover the hidden mystery by looking at the science and mathematics associated with it. In this book, great care has been taken to explain the concepts and techniques associated with deep learning from a mathematical as well as a scientific viewpoint. Also, the first chapter is totally dedicated toward building the mathematical base required to comprehend deeplearning concepts with ease. TensorFlow has been chosen as the deeplearning package because of its flexibility for research purposes and its ease of use. Another reason for choosing TensorFlow is its capability to load models with ease in a live production environment using its serving capabilities. In summary, Pro Deep Learning with TensorFlow provides practical, handson expertise so you can learn deep learning from scratch and deploy meaningful deeplearning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deeplearning architectures. All the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deeplearning applications. The code presented in the book is available in the form of iPython notebooks and scripts that allow you to try out examples and extend them in interesting ways. You will be equipped with the mathematical foundation and scientific knowledge to pursue research in this field and give back to the community.
 6.19MB
Deep Learning with TensorFlow
20170816Key Features, Learn advanced techniques in deep learning with this examplerich guide on Google's brainchildExplore various neural networks with the help of this comprehensive guideAdvanced guide on machine learning techniques, in particular TensorFlow for deep learning., Book Description, Deep learning is the next step after machine learning. It is machine learning but with a more advanced implementation. As machine learning is no longer an academic topic, but a mainstream practice, deep learning has taken a front seat. With deep learning being used by many data scientists, deeper neural networks are evaluated for accurate results. Data scientists want to explore data abstraction layers and this book will be their guide on this journey. This book evaluates common, and not so common, deep neural networks and shows how these can be exploited in the real world with complex raw data using TensorFlow., The book will take you through an understanding of the current machine learning landscape then delve into TensorFlow and how to use it by considering various data sets and use cases. Throughout the chapters, you'll learn how to implement various deep learning algorithms for your machine learning systems and integrate them into your product offerings such as search, image recognition, and language processing. Additionally, we'll examine its performance by optimizing it with respect to its various parameters, comparing it against benchmarks along with teaching machines to learn from the information and determine the ideal behavior within a specific context, in order to maximize its performance., After finishing the book, you will be familiar with machine learning techniques, in particular TensorFlow for deep learning, and will be ready to apply some of your knowledge in a real project either in a research or commercial setting., What you will learn, Provide an overview of the machine learning landscapeLook at the historical development and progress of deep learningDescribe TensorFlow and become very familiar with it both in theory and in practiceAccess public datasets and use TF to load, process, clean, and transform dataUse TensorFlow on realworld data sets including images and textGet familiar with TensorFlow by applying it in various hands on exercises using the command lineEvaluate the performance of your deep learning modelsQuickly teach machines to learn from data by exploring reinforcement learning techniques.Understand how this technology is being used in the real world by exploring active areas of deep learning research and application.
 7.13MB
Deep learning with tensorflow
20171107Key Features, Learn advanced techniques in deep learning with this examplerich guide on Google's brainchildExplore various neural networks with the help of this comprehensive guideAdvanced guide on machine learning techniques, in particular TensorFlow for deep learning., Book Description, Deep learning is the next step after machine learning. It is machine learning but with a more advanced implementation. As machine learning is no longer an academic topic, but a mainstream practice, deep learning has taken a front seat. With deep learning being used by many data scientists, deeper neural networks are evaluated for accurate results. Data scientists want to explore data abstraction layers and this book will be their guide on this journey. This book evaluates common, and not so common, deep neural networks and shows how these can be exploited in the real world with complex raw data using TensorFlow., The book will take you through an understanding of the current machine learning landscape then delve into TensorFlow and how to use it by considering various data sets and use cases. Throughout the chapters, you'll learn how to implement various deep learning algorithms for your machine learning systems and integrate them into your product offerings such as search, image recognition, and language processing. Additionally, we'll examine its performance by optimizing it with respect to its various parameters, comparing it against benchmarks along with teaching machines to learn from the information and determine the ideal behavior within a specific context, in order to maximize its performance., After finishing the book, you will be familiar with machine learning techniques, in particular TensorFlow for deep learning, and will be ready to apply some of your knowledge in a real project either in a research or commercial setting., What you will learn, Provide an overview of the machine learning landscapeLook at the historical development and progress of deep learningDescribe TensorFlow and become very familiar with it both in theory and in practiceAccess public datasets and use TF to load, process, clean, and transform dataUse TensorFlow on realworld data sets including images and textGet familiar with TensorFlow by applying it in various hands on exercises using the command lineEvaluate the performance of your deep learning modelsQuickly teach machines to learn from data by exploring reinforcement learning techniques.Understand how this technology is being used in the real world by exploring active areas of deep learning research and application.
 13.54MB
Deep Learning with TensorFlow 第二版
20180418Deep Learning with TensorFlow Second Edition 2018 Packt Publishing
 7.18MB
Pro Deep Learning with TensorFlow A Mathematical Approach to Advanced epub
20171229Pro Deep Learning with TensorFlow A Mathematical Approach to Advanced Artificial Intelligence in Python 英文epub 本资源转载自网络，如有侵权，请联系上传者或csdn删除 查看此书详细信息请在美国亚马逊官网搜索此书
 7.6MB
Deep Learning with Tensorflow
20180822该书籍是2017年Deep Learning with Tensorflow，主要在应用和理论的讲解，包含代码，非常适合初学者入门学习。
 1.30MB
HandsOn Deep Learning with TensorFlow 随书代码
20170805HandsOn Deep Learning with TensorFlow Dan Van Boxel July 2017 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.
 18.82MB
《deep learning with tensorflow》随书源码
20180106《deep learning with tensorflow》随书源码，想要学习tensorflow的朋友可以看看
 8.56MB
Machine Learning with TensorFlow.pdf
19560502Machine Learning with TensorFlow gives readers a solid foundation in machinelearning concepts plus handson experience coding TensorFlow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology TensorFlow, Google's library for largescale machine learning, simplifies oftencomplex computations by representing them as graphs and efficiently mapping parts of the graphs to machines in a cluster or to the processors of a single machine. About the Book Machine Learning with TensorFlow gives readers a solid foundation in machinelearning concepts plus handson 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 deeplearning concepts like autoencoders, recurrent neural networks, and reinforcement learning. Digest this book and you will be ready to use TensorFlow for machinelearning and deeplearning applications of your own. What's Inside Matching your tasks to the right machinelearning and deeplearning approachesVisualizing algorithms with TensorBoardUnderstanding and using neural networks About the Reader Written for developers experienced with Python and algebraic concepts like vectors and matrices. About the Author Author Nishant Shukla is a computer vision researcher focused on applying machinelearning techniques in robotics. Senior technical editor, Kenneth Fricklas, is a seasoned developer, author, and machinelearning practitioner. Table of Contents PART 1  YOUR MACHINELEARNING RIGA machinelearning odysseyTensorFlow essentialsPART 2  CORE LEARNING ALGORITHMSLinear regression and beyondA gentle introduction to classificationAutomatically clustering dataHidden Markov models PART 3  THE NEURAL NETWORK PARADIGMA peek into autoencodersReinforcement learningConvolutional neural networksRecurrent neural networksSeque
 17.19MB
Deep Learning with TensorFlow, 2nd EditionPackt Publishing(2018).epub
20180414Every week, we follow news of applications and the shocking results obtained from them, thanks to the artificial intelligence algorithms applied in different fields. What we are witnessing is one of the biggest accelerations in the entire history of this sector, and the main suspect behind these important developments is called deep learning. Deep learning comprises a vast set of algorithms that are based on the concept of neural networks and expand to contain a huge number of nodes that are disseminated at several levels of depth. Though the concept of neural networks, the socalled Artificial Neural Network (ANN), dates back to the late 1940s, initially, they were difficult to be used because of the need for huge computational power resources and the lack of data required to train the algorithms. Presently, the ability to use graphics processors (GPUs) in parallel to perform intensive calculation operations has completely opened the way to the use of deep learning. In this context, we propose the second edition of this book, with expanded and revised contents that introduce the core concepts of deep learning, using the last version of TensorFlow.
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Java基础与实践
20180731Java语言是目前流行的一门程序设计语言。本课程是一套全面讲解Java语言程序设计的开发类课程，由浅入深地介绍Java基础内容，主要包括基本类型及运算符、控制执行流程、字符串、面向对象、集合与数组、文件及流、异常、多线程等完整的Java知识体系。
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基于SSM技术的在线商城系统[实战视频]
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SpringBoot实战教程：SpringBoot企业级线上商城项目讲解
20190927<div style="color:rgba(0,0,0,.75);"> <span style="color:#4d4d4d;"> </span> <div style="color:rgba(0,0,0,.75);"> <span style="color:#4d4d4d;"> </span> <div style="color:rgba(0,0,0,.75);"> <div style="color:rgba(0,0,0,.75);"> <span style="color:#4d4d4d;">当前课程中商城项目的实战源码是我发布在 GitHub 上的开源项目 newbeemall （新蜂商城），目前已有 6300 多个 star，</span><span style="color:#4d4d4d;">本课程是一个 Spring Boot 技术栈的实战类课程，课程共分为 3 大部分，前面两个部分为基础环境准备和相关概念介绍，第三个部分是 Spring Boot 商城项目功能的讲解，让大家实际操作并实践上手一个大型的线上商城项目，并学习到一定的开发经验以及其中的开发技巧。<br /> 商城项目所涉及的功能结构图整理如下：<br /> </span> </div> <div style="color:rgba(0,0,0,.75);"> </div> <div style="color:rgba(0,0,0,.75);"> <p style="color:#4d4d4d;"> <img alt="modules" src="https://imgconvert.csdnimg.cn/aHR0cHM6Ly9uZXdiZWUtbWFsbC5vc3MtY24tYmVpamluZy5hbGl5dW5jcy5jb20vcG9zdGVyL3N0b3JlL25ld2JlZS1tYWxsLXMucG5n?xossprocess=image/format,png" /> </p> </div> <p style="color:rgba(0,0,0,.75);"> <strong><span style="color:#e53333;">课程特色</span></strong> </p> <p style="color:rgba(0,0,0,.75);"> </p> <div style="color:rgba(0,0,0,.75);"> </div> <div style="color:rgba(0,0,0,.75);"> <ul> <li> 对新手开发者十分友好，无需复杂的操作步骤，仅需 2 秒就可以启动这个完整的商城项目 </li> <li> 最终的实战项目是一个企业级别的 Spring Boot 大型项目，对于各个阶段的 Java 开发者都是极佳的选择 </li> <li> 实践项目页面美观且实用，交互效果完美 </li> <li> 教程详细开发教程详细完整、文档资源齐全 </li> <li> 代码+讲解+演示网站全方位保证，向 Hello World 教程说拜拜 </li> <li> 技术栈新颖且知识点丰富，学习后可以提升大家对于知识的理解和掌握，可以进一步提升你的市场竞争力 </li> </ul> </div> <p style="color:rgba(0,0,0,.75);"> </p> <p style="color:rgba(0,0,0,.75);"> <span style="color:#e53333;">课程预览</span> </p> <p style="color:rgba(0,0,0,.75);"> </p> <div style="color:rgba(0,0,0,.75);"> </div> <div style="color:rgba(0,0,0,.75);"> <p style="color:#4d4d4d;"> 以下为商城项目的页面和功能展示，分别为： </p> </div> <div style="color:rgba(0,0,0,.75);"> <ul> <li> 商城首页 1<br /> <img alt="" src="https://imgbss.csdnimg.cn/202103050347585499.gif" /> </li> <li> 商城首页 2<br /> <img alt="" src="https://imgbss.csdn.net/202005181054413605.png" /> </li> <li> </li> <li> 购物车<br /> <img alt="cart" src="https://imgconvert.csdnimg.cn/aHR0cHM6Ly9uZXdiZWUtbWFsbC5vc3MtY24tYmVpamluZy5hbGl5dW5jcy5jb20vcG9zdGVyL3Byb2R1Y3QvY2FydC5wbmc?xossprocess=image/format,png" /> </li> <li> 订单结算<br /> <img alt="settle" src="https://imgconvert.csdnimg.cn/aHR0cHM6Ly9uZXdiZWUtbWFsbC5vc3MtY24tYmVpamluZy5hbGl5dW5jcy5jb20vcG9zdGVyL3Byb2R1Y3Qvc2V0dGxlLnBuZw?xossprocess=image/format,png" /> </li> <li> 订单列表<br /> <img alt="orders" src="https://imgconvert.csdnimg.cn/aHR0cHM6Ly9uZXdiZWUtbWFsbC5vc3MtY24tYmVpamluZy5hbGl5dW5jcy5jb20vcG9zdGVyL3Byb2R1Y3Qvb3JkZXJzLnBuZw?xossprocess=image/format,png" /> </li> <li> 支付页面<br /> <img alt="" src="https://imgbss.csdn.net/201909280301493716.jpg" /> </li> <li> 后台管理系统登录页<br /> <img alt="login" src="https://imgconvert.csdnimg.cn/aHR0cHM6Ly9uZXdiZWUtbWFsbC5vc3MtY24tYmVpamluZy5hbGl5dW5jcy5jb20vcG9zdGVyL3Byb2R1Y3QvbWFuYWdlLWxvZ2luLnBuZw?xossprocess=image/format,png" /> </li> <li> 商品管理<br /> <img alt="goods" src="https://imgconvert.csdnimg.cn/aHR0cHM6Ly9uZXdiZWUtbWFsbC5vc3MtY24tYmVpamluZy5hbGl5dW5jcy5jb20vcG9zdGVyL3Byb2R1Y3QvbWFuYWdlLWdvb2RzLnBuZw?xossprocess=image/format,png" /> </li> <li> 商品编辑<br /> <img alt="" src="https://imgbss.csdnimg.cn/202103050348242799.png" /> </li> </ul> </div> </div> </div> </div>

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