Data Science on AWS: Implementing End-To-End, Continuous AI and Machine Learning Pipelines
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Step-by-step pipeline building and deployment for AWS AI and ML stack enables efficient project setup
Automated machine learning (AutoML) integration with SageMaker AutoPilot streamlines specific use cases
Real-time ML anomaly detection and streaming analytics using Amazon Kinesis and Kafka provide actionable insights
Security best practices including IAM, authentication, and authorization ensure robust data protection
Case studies on NLP, computer vision, and fraud detection demonstrate practical application
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With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level up your skills. This guide shows you how to build and run p