tensorflow for machine intelligence

Download Book Tensorflow For Machine Intelligence in PDF format. You can Read Online Tensorflow For Machine Intelligence here in PDF, EPUB, Mobi or Docx formats.

Tensorflow Machine Learning Cookbook

Author : Nick McClure
ISBN : 1786462168
Genre :
File Size : 39. 43 MB
Format : PDF, ePub
Download : 673
Read : 624

Download Now Read Online


Cook up the machine learning recipe of your choice using the latest numerical computing library-TensorFlow-with the help of this easy-to-follow cookbookAbout This Book* Your quick guide to implementing TensorFlow in your day-to-day machine learning activities* Learn advanced techniques that bring more accuracy and speed to machine learning with the help of this cookbook* Upgrade yourself to the second generation of machine learning with this guide on TensorFlowWho This Book Is ForThis book caters to data scientists who are familiar with C++ or Python and perform machine learning activities on a day-to-day basis. This book is for both intermediate as well as advanced machine learning implementers who need a quick guide they can easily navigate through.What You Will Learn* Become familiar with the basics of the TensorFlow machine learning library* Get to know Linear Regression techniques with TensorFlow* Learn SVM's with practical hands-on recipes* Implement neural networks and improve predictions* Apply NLP and sentiment analysis to your data* Master CNN and RNN through real-world recipes* Take TensorFlow into productionIn DetailTensorFlow 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 help you gain more insights into your data than ever before. You'll work through recipes on training models, model evaluation, sentiment analysis, regression analysis, clustering analysis, artificial neural networks, and deep learning, each using Google's machine learning library TensorFlow.We'll start with the fundamentals of the TensorFlow library and you will learn about variables, matrices, and various data sources. Moving ahead, you will get hands-on experience of Linear Regression techniques with TensorFlow. The next chapters cover important high-level concepts such as neural networks, CNN, RNN, and NLP through real-world examples in every recipe.Once you are well versed with the TensorFlow ecosystem, the last chapter will teach you to take it to production.

Machine Learning With Tensorflow

Author : Nishant Shukla
ISBN : 1617293873
Genre : Computers
File Size : 56. 85 MB
Format : PDF, ePub
Download : 942
Read : 198

Download Now Read Online


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 applications? The answer is TensorFlow, a new open source machine learning library from Google. The TensorFlow library can take your high level designs and turn them into the low level mathematical operations required by machine learning algorithms. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. Machine Learning with TensorFlow teaches readers about machine learning algorithms and how to implement solutions with TensorFlow. It starts with an overview of machine learning concepts and moves on to the essentials needed to begin using TensorFlow. Each chapter zooms into a prominent example of machine learning. Readers can cover them all to master the basics or skip around to cater to their needs. By the end of this book, readers will be able to solve classification, clustering, regression, and prediction problems in the real world.

Getting Started With Tensorflow

Author : Giancarlo Zaccone
ISBN : 1786468573
Genre : Computers
File Size : 42. 58 MB
Format : PDF, ePub, Mobi
Download : 269
Read : 953

Download Now Read Online


Get up and running with the latest numerical computing library by Google and dive deeper into your data!About This Book- Get the first book on the market that shows you the key aspects TensorFlow, how it works, and how to use it for the second generation of machine learning- Want to perform faster and more accurate computations in the field of data science? This book will acquaint you with an all-new refreshing library-TensorFlow!- Dive into the next generation of numerical computing and get the most out of your data with this quick guideWho This Book Is ForThis book is dedicated to all the machine learning and deep learning enthusiasts, data scientists, researchers, and even students who want to perform more accurate, fast machine learning operations with TensorFlow. Those with basic knowledge of programming (Python and C/C++) and math concepts who want to be introduced to the topics of machine learning will find this book useful.What You Will Learn- Install and adopt TensorFlow in your Python environment to solve mathematical problems- Get to know the basic machine and deep learning concepts- Train and test neural networks to fit your data model- Make predictions using regression algorithms- Analyze your data with a clustering procedure- Develop algorithms for clustering and data classification- Use GPU computing to analyze big dataIn DetailGoogle'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 networks.This book takes you through the practical software implementation of various machine learning techniques with TensorFlow. In the first few chapters, you'll gain familiarity with the framework and perform the mathematical operations required for data analysis. As you progress further, you'll learn to implement various machine learning techniques such as classification, clustering, neural networks, and deep learning through practical examples.By the end of this book, you'll have gained hands-on experience of using TensorFlow and building classification, image recognition systems, language processing, and information retrieving systems for your application.Style and approachGet quickly up and running with TensorFlow using this fast-paced guide. You will get to know everything that can be done with TensorFlow and we'll show you how to implement it in your environment. The examples in the book are from the core of the computation industry-something you can connect to and will find familiar.

Scala For Machine Learning

Author : Patrick R. Nicolas
ISBN : 9781783558759
Genre : Computers
File Size : 40. 51 MB
Format : PDF
Download : 381
Read : 453

Download Now Read Online


Are you curious about AI? All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book!

Fundamentals Of Deep Learning

Author : Nikhil Buduma
ISBN : 1491925612
Genre :
File Size : 70. 74 MB
Format : PDF, ePub, Mobi
Download : 309
Read : 321

Download Now Read Online


With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field. Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started.

An Introduction To Neural Networks

Author : Kevin Gurney
ISBN : 9780203451519
Genre : Computers
File Size : 45. 17 MB
Format : PDF, ePub, Docs
Download : 387
Read : 686

Download Now Read Online


Though mathematical ideas underpin the study of neural networks, the author presents the fundamentals without the full mathematical apparatus. All aspects of the field are tackled, including artificial neurons as models of their real counterparts; the geometry of network action in pattern space; gradient descent methods, including back-propagation; associative memory and Hopfield nets; and self-organization and feature maps. The traditionally difficult topic of adaptive resonance theory is clarified within a hierarchical description of its operation. The book also includes several real-world examples to provide a concrete focus. This should enhance its appeal to those involved in the design, construction and management of networks in commercial environments and who wish to improve their understanding of network simulator packages. As a comprehensive and highly accessible introduction to one of the most important topics in cognitive and computer science, this volume should interest a wide range of readers, both students and professionals, in cognitive science, psychology, computer science and electrical engineering.

The Datacenter As A Computer

Author : Luiz André Barroso
ISBN : 9781598295566
Genre : Computers
File Size : 22. 60 MB
Format : PDF, ePub, Docs
Download : 322
Read : 812

Download Now Read Online


As computation continues to move into the cloud, the computing platform of interest no longer resembles a pizza box or a refrigerator, but a warehouse full of computers. These new large datacenters are quite different from traditional hosting facilities of earlier times and cannot be viewed simply as a collection of co-located servers. Large portions of the hardware and software resources in these facilities must work in concert to efficiently deliver good levels of Internet service performance, something that can only be achieved by a holistic approach to their design and deployment. In other words, we must treat the datacenter itself as one massive warehouse-scale computer (WSe. We describe the architecture of WSCs, the main factors influencing their design, operation, and cost structure, and the characteristics of their software base. We hope it will be useful to architects and programmers of today's WSCs, as well as those of future many-core platforms which may one day implement the equivalent of today's WSCs on a single board. Table of Contents: Introduction / Workloads and Software Infrastructure / Hardware Building Blocks / Datacenter Basics / Energy and Power Efficiency / Modeling Costs / Dealing with Failures and Repairs / Closing Remarks

Top Download:

New Books