Generative AI on AWS: Building Context-Aware Multimodal Reasoning Applications

Computers & Technology

Fregly, Chris

Barth, Antje

Eigenbrode, Shelbee

Computer Science

O'Reilly Media

<p><div> <p>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 pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance.</p> <ul> <li>Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more</li> <li>Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot</li> <li>Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment</li> <li>Tie everything together into a repeatable machine learning operations pipeline</li> <li>Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka</li> <li>Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more</li> </ul> </div></p>

Data Science on AWS: Implementing End-to-End, Continuous AI and Machine Learning Pipelines

Business & Money

Education & Reference

AWS de hajimeru seisei AI: RAG apurikēshon kaihatsu kara, kiban moderu no bichōsei, maruchimōdaru AI katsuyō made o tameshite manabu

Orairī Japan

IA generativa en AWS: Creación de aplicaciones multimodales

Reference

Marcombo

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