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Deep Learning Pipeline : Building a Deep Learning Model with TensorFlow by Mahmoud Hamdy and Hisham El-Amir (2019, Trade Paperback)
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Publication Date: 1/24/2020. Condition Guide. Your Privacy. ISBN: 9781484253489. By El-Amir, Hisham. Your source for quality books at reduced prices. Item Availability.
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About this product
Product Identifiers
PublisherApress L. P.
ISBN-101484253485
ISBN-139781484253489
eBay Product ID (ePID)5038386802
Product Key Features
Number of PagesXxv, 551 Pages
Publication NameDeep Learning Pipeline : Building a Deep Learning Model with Tensorflow
LanguageEnglish
Publication Year2019
SubjectIntelligence (Ai) & Semantics
TypeTextbook
Subject AreaComputers
AuthorMahmoud Hamdy, Hisham El-Amir
FormatTrade Paperback
Dimensions
Item Weight31 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Number of Volumes1 vol.
IllustratedYes
Table Of ContentDeep Learning Pipeline Part One: Introduction.- Chapter 1: A Gentle Introduction.- Chapter 2: Setting up Your Environment .- Chapter 3: A Nice Tour Through Deep Learning Pipeline .- Part Two: Data.- Chapter 4: Build your first Toy TensorFlow App.- Chapter 5: Defining Data .- Chapter 6: Data Wrangling and Preprocessing.- Chapter 7: Data Resampling .- Part Three: TensorFlow.- Chapter 8: Feature Selection and Feature Engineering .- Chapter 9: Deep Learning Fundamentals.- Chapter 10: Improving Deep Neural Network.- Chapter 11: Convolutional Neural Networks.- Part Four: Applications and Appendix.- Chapter 12: Sequential Models .- Chapter 13: Selected Topics in Computer vision.- Chapter 14: Selected Topics in Natural Language Processing.- Chapter 15: Applications.
SynopsisBuild your own pipeline based on modern TensorFlow approaches rather than outdated engineering concepts.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 basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets. You'll also develop a deep learning project by preparing data, choosing the model that fits that data, and debugging your model to get the best fit to data all using Tensorflow techniques. Enhance your skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution or entering a Kaggle contest, Deep Learning Pipeline is for you! What You'll Learn Develop a deep learning project using data Study and apply various models to your data Debug and troubleshoot the proper model suited for your data Who This Book Is For Developers, analysts, and data scientists looking to add to or enhance their existing skills by accessing some of the most powerful recent trends in data science. Prior experience in Python or other TensorFlow related languages and mathematics would be helpful., 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 basic Tensorflow obstacles to easily create functional apps and deploy well-trained models. Step-by-step and example-oriented instructions help you understand each step of the deep learning pipeline while you apply the most straightforward and effective tools to demonstrative problems and datasets. You'll also develop a deep learning project by preparing data, choosing the model that fits that data, and debugging your model to get the best fit to data all using Tensorflow techniques. Enhance your skills by accessing some of the most powerful recent trends in data science. If you've ever considered building your own image or text-tagging solution or entering a Kaggle contest, Deep Learning Pipeline is for you What You'll Learn Develop a deep learning project using data Study and apply various models to your data Debug and troubleshoot the proper model suited for your data Who This Book Is For Developers, analysts, and data scientists looking to add to or enhance their existing skills by accessing some of the most powerful recent trends in data science. Prior experience in Python or other TensorFlow related languages and mathematics would be helpful.
LC Classification NumberQ334-342
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