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Building Scalable Deep Learning Pipelines on AWS : Develop, Train, and Deploy Deep Learning Models

By: Abdelaziz Testas (Author)

Not yet Published

Ksh 10,250.00

Format: Paperback or Softback

ISBN-10: 886881016Y

ISBN-13: 9798868810169

Publisher: Springer-Verlag Berlin and Heidelberg GmbH & Co. KG

Imprint: APress

Country of Manufacture: GB

Country of Publication: GB

Publication Date: Nov 29th, 2024

Publication Status: Active

Product extent: 760 Pages

Product Classification / Subject(s): Programming & scripting languages: general
Machine learning

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  • Description

  • Reviews

This book is your comprehensive guide to creating powerful, end-to-end deep learning workflows on Amazon Web Services (AWS). The book explores how to integrate essential big data tools and technologies—such as PySpark, PyTorch, TensorFlow, Airflow, EC2, and S3—to streamline the development, training, and deployment of deep learning models. Starting with the importance of scaling advanced machine learning models, this book leverages AWS's robust infrastructure and comprehensive suite of services. It guides you through the setup and configuration needed to maximize the potential of deep learning technologies. You will gain in-depth knowledge of building deep learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment. The book provides insights into setting up an AWS environment, configuring necessary tools, and using PySpark for distributed data processing. You will also delve into hands-on tutorials for PyTorch and TensorFlow, mastering their roles in building and training neural networks. Additionally, you will learn how Apache Airflow can orchestrate complex workflows and how Amazon S3 and EC2 enhance model deployment at scale. By the end of this book, you will be equipped to tackle real-world challenges and seize opportunities in the rapidly evolving field of deep learning with AWS. You will gain the insights and skills needed to drive innovation and maintain a competitive edge in today’s data-driven landscape.  What You Will LearnMaximize  AWS services for scalable and high-performance deep learning architecturesHarness the capacity of PyTorch and TensorFlow for advanced neural network developmentUtilize PySpark for efficient distributed data processing on AWSOrchestrate complex workflows with Apache Airflow for seamless data processing, model training, and deployment Who This Book Is ForData scientists looking to expand their skill set to include deep learning on AWS, machine learning engineers tasked with designing and deploying machine learning systems who want to incorporate deep learning capabilities into their applications, AI practitioners working across various industries who seek to leverage deep learning for solving complex problems and gaining a competitive advantage 

This book is your comprehensive guide to creating powerful, end-to-end deep learning workflows on Amazon Web Services (AWS). The book explores how to integrate essential big data tools and technologies—such as PySpark, PyTorch, TensorFlow, Airflow, EC2, and S3—to streamline the development, training, and deployment of deep learning models.

Starting with the importance of scaling advanced machine learning models, this book leverages AWS''s robust infrastructure and comprehensive suite of services. It guides you through the setup and configuration needed to maximize the potential of deep learning technologies. You will gain in-depth knowledge of building deep learning pipelines, including data preprocessing, feature engineering, model training, evaluation, and deployment.

The book provides insights into setting up an AWS environment, configuring necessary tools, and using PySpark for distributed data processing. You will also delve into hands-on tutorials for PyTorch and TensorFlow, mastering their roles in building and training neural networks. Additionally, you will learn how Apache Airflow can orchestrate complex workflows and how Amazon S3 and EC2 enhance model deployment at scale.

By the end of this book, you will be equipped to tackle real-world challenges and seize opportunities in the rapidly evolving field of deep learning with AWS. You will gain the insights and skills needed to drive innovation and maintain a competitive edge in today’s data-driven landscape.

 

What You Will Learn

  • Maximize  AWS services for scalable and high-performance deep learning architectures
  • Harness the capacity of PyTorch and TensorFlow for advanced neural network development
  • Utilize PySpark for efficient distributed data processing on AWS
  • Orchestrate complex workflows with Apache Airflow for seamless data processing, model training, and deployment

 

Who This Book Is For

Data scientists looking to expand their skill set to include deep learning on AWS, machine learning engineers tasked with designing and deploying machine learning systems who want to incorporate deep learning capabilities into their applications, AI practitioners working across various industries who seek to leverage deep learning for solving complex problems and gaining a competitive advantage

 

Get Building Scalable Deep Learning Pipelines on AWS by at the best price and quality guranteed only at Werezi Africa largest book ecommerce store. The book was published by Springer-Verlag Berlin and Heidelberg GmbH & Co. KG and it has pages. Enjoy Shopping Best Offers & Deals on books Online from Werezi - Receive at your doorstep - Fast Delivery - Secure mode of Payment

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