Building Scalable Deep Learning Pipelines by Abdelaziz Testas (.PDF)+

File Size: 10 MB

Building Scalable Deep Learning Pipelines on AWS: Develop, Train, and Deploy Deep Learning Models by Abdelaziz Testas
Requirements: .ePUB, .PDF reader, 10 MB
Overview: 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.
Genre: Non-Fiction > Tech & Devices

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