Learning TensorFlow (häftad)
Fler böcker inom
Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
242
Utgivningsdatum
2017-09-12
Upplaga
1
Förlag
O'Reilly Media, Inc, USA
Dimensioner
234 x 177 x 12 mm
Vikt
385 g
Antal komponenter
1
SAB
Pubb
ISBN
9781491978511
Learning TensorFlow (häftad)

Learning TensorFlow

A Guide to Building Deep Learning Systems

Häftad Engelska, 2017-09-12
399
Skickas inom 5-8 vardagar.
Fri frakt inom Sverige för privatpersoner.
Finns även som
Visa alla 2 format & utgåvor
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, natural language processing (NLP), speech recognition, and general predictive analytics. Authors Tom Hope, Yehezkel Resheff, and Itay Lieder provide a hands-on approach to TensorFlow fundamentals for a broad technical audience-from data scientists and engineers to students and researchers. You'll begin by working through some basic examples in TensorFlow before diving deeper into topics such as neural network architectures, TensorBoard visualization, TensorFlow abstraction libraries, and multithreaded input pipelines. Once you finish this book, you'll know how to build and deploy production-ready deep learning systems in TensorFlow. Get up and running with TensorFlow, rapidly and painlessly Learn how to use TensorFlow to build deep learning models from the ground up Train popular deep learning models for computer vision and NLP Use extensive abstraction libraries to make development easier and faster Learn how to scale TensorFlow, and use clusters to distribute model training Deploy TensorFlow in a production setting
Visa hela texten

Passar bra ihop

  1. Learning TensorFlow
  2. +
  3. Deep Learning

De som köpt den här boken har ofta också köpt Deep Learning av Josh Patterson, Adam Gibson (häftad).

Köp båda 2 för 798 kr

Kundrecensioner

Har du läst boken? Sätt ditt betyg »

Fler böcker av författarna

Bloggat om Learning TensorFlow

Övrig information

Tom Hope is an applied machine learning researcher and data scientist with extensive background in academia and industry.He has background as a senior data scientist in large international corporation settings, leading data science and deep learning R&D across multiple domains including web mining, text analytics, computer vision, sales and marketing, IoT, financial forecasting and large-scale manufacturing. Previously he was at a successful e-commerce startup in its early days, leading data science R&D. He has also served as a data science consultant for major international companies and startups. His research in computer science, data mining and statistics revolves around machine learning, deep learning, NLP, weak supervision and time-series.Hezi Reshef is an applied researcher and PhD student in Machine Learning at the Hebrew University, developing Machine Learning and Deep Learning methods for wearable device data, and working on using wearable devices to monitor patient health. He has worked at Intel Corp., leading Deep Learning R&D for monitoring and predicting patient outcomes using remote sensing and wearables. Prior to Intel, Hezi was at Microsoft, leading Machine Learning R&D for mining telemetry data, predicting software bugs, user segmentation, and other projects.Itay Lieder is an applied researcher in Machine Learning and Computational Neuroscience and a PhD student at the Hebrew University, in collaboration with the Gatsby Computational Neuroscience Unit at UCL, studying the human perception with massive crowd-sourcing experiments on Amazon Turk. His current work focuses on predicting and understanding the way humans react to sounds (e.g. music), via multiple online interactive experiments. He has worked for large international corporations, leading Deep Learning R&D in text analytics and web mining for sales and marketing.