Deploying Secure Data Science Apps by Lucas H. Benevides e Braga(.PDF)

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File Size: 21.1 MB

Deploying Secure Data Science Applications in the Cloud: From VMs to Serverless with AWS and Google Cloud by Lucas H. Benevides e Braga
Requirements: .PDF reader, 21.1 MB
Overview: This step-by-step guide is for Data Scientists, ML engineers, and DevOps practitioners who need to turn prototypes into secure, scalable production services on AWS and Google Cloud. With step-by-step instructions and practical examples, this book bridges the gap between building Data Science applications and Machine Learning models, and deploying them effectively in real-world scenarios. The book begins with an introduction to essential cloud concepts, providing detailed guidance on setting up a virtual machine (VM) on AWS—and later on Google Cloud—to serve applications. This includes configuring security groups and establishing secure SSH (Secure Shell) connections using VSCode (Visual Studio Code). You will learn how to deploy a dummy HTTP Streamlit application as a foundational exercise before advancing to more complex setups. For beginning to intermediate professionals with a basic understanding of Python, including Data Scientists, ML Engineers, Data Engineers, and Data Analysts who aim to securely deploy their projects in production environments, and individuals working on both personal projects and enterprise-level solutions, leveraging AWS and Google Cloud setups.
Genre: Non-Fiction > Tech & Devices

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