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Generative AI on AWS

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Release : 2023-11-13
Genre : Computers
Kind : eBook
Book Rating : 195/5 ( reviews)

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Book Synopsis Generative AI on AWS by : Chris Fregly

Download or read book Generative AI on AWS written by Chris Fregly. This book was released on 2023-11-13. Available in PDF, EPUB and Kindle. Book excerpt: Companies today are moving rapidly to integrate generative AI into their products and services. But there's a great deal of hype (and misunderstanding) about the impact and promise of this technology. With this book, Chris Fregly, Antje Barth, and Shelbee Eigenbrode from AWS help CTOs, ML practitioners, application developers, business analysts, data engineers, and data scientists find practical ways to use this exciting new technology. You'll learn the generative AI project life cycle including use case definition, model selection, model fine-tuning, retrieval-augmented generation, reinforcement learning from human feedback, and model quantization, optimization, and deployment. And you'll explore different types of models including large language models (LLMs) and multimodal models such as Stable Diffusion for generating images and Flamingo/IDEFICS for answering questions about images. Apply generative AI to your business use cases Determine which generative AI models are best suited to your task Perform prompt engineering and in-context learning Fine-tune generative AI models on your datasets with low-rank adaptation (LoRA) Align generative AI models to human values with reinforcement learning from human feedback (RLHF) Augment your model with retrieval-augmented generation (RAG) Explore libraries such as LangChain and ReAct to develop agents and actions Build generative AI applications with Amazon Bedrock

Tutorials - Building Generative AI-Based Applications on AWS Bedrock - Step by step with code

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Genre : Computers
Kind : eBook
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Book Synopsis Tutorials - Building Generative AI-Based Applications on AWS Bedrock - Step by step with code by : Anand Vemula

Download or read book Tutorials - Building Generative AI-Based Applications on AWS Bedrock - Step by step with code written by Anand Vemula. This book was released on . Available in PDF, EPUB and Kindle. Book excerpt: "Tutorials - Building Generative AI-Based Applications on AWS Bedrock" is an insightful guide designed to walk readers through the process of creating AI-powered applications using AWS infrastructure. Authored by experts in the field, this book offers a step-by-step approach combined with practical code examples to help developers harness the power of generative AI on the AWS platform. The book begins by introducing readers to the foundational concepts of generative AI and its real-world applications. It provides a clear understanding of how generative AI works and its potential to transform various industries, from art and design to healthcare and finance. Moving forward, the tutorials dive into the specifics of building AI-based applications on AWS Bedrock, Amazon's suite of services for machine learning and AI. Readers are guided through setting up their AWS environment, including creating and configuring necessary resources such as EC2 instances, S3 buckets, and IAM roles. The tutorials then proceed to cover key components of generative AI, such as deep learning frameworks like TensorFlow and PyTorch. Readers learn how to train and deploy generative models using AWS SageMaker, Amazon's managed machine learning service, ensuring scalability and efficiency in their applications. Throughout the book, code examples are provided to illustrate each step of the process, making it easy for readers to follow along and implement the techniques in their own projects. From data preprocessing and model training to inference and evaluation, the tutorials cover the entire AI development lifecycle on AWS Bedrock. Moreover, the book addresses common challenges and best practices for building robust and reliable AI applications in a cloud environment. Topics such as data security, model optimization, and cost management are discussed to help readers overcome potential hurdles and optimize their workflows. By the end of the tutorials, readers will have gained a comprehensive understanding of how to leverage AWS Bedrock to build powerful generative AI-based applications. Whether they are seasoned AI practitioners or newcomers to the field, this book equips readers with the knowledge and skills needed to harness the full potential of AI on the AWS platform. In summary, "Tutorials - Building Generative AI-Based Applications on AWS Bedrock" is an invaluable resource for developers looking to explore the intersection of generative AI and cloud computing, offering practical guidance and code samples to accelerate their journey towards building innovative AI solutions.

GenAI on AWS

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Author :
Release : 2024-11-27
Genre : Computers
Kind : eBook
Book Rating : 282/5 ( reviews)

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Book Synopsis GenAI on AWS by : Asif Abbasi

Download or read book GenAI on AWS written by Asif Abbasi. This book was released on 2024-11-27. Available in PDF, EPUB and Kindle. Book excerpt:

Cloud Native AI and Machine Learning on AWS

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Author :
Release : 2023-02-14
Genre : Computers
Kind : eBook
Book Rating : 267/5 ( reviews)

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Book Synopsis Cloud Native AI and Machine Learning on AWS by : Premkumar Rangarajan

Download or read book Cloud Native AI and Machine Learning on AWS written by Premkumar Rangarajan. This book was released on 2023-02-14. Available in PDF, EPUB and Kindle. Book excerpt: Bring elasticity and innovation to Machine Learning and AI operations KEY FEATURES ● Coverage includes a wide range of AWS AI and ML services to help you speedily get fully operational with ML. ● Packed with real-world examples, practical guides, and expert data science methods for improving AI/ML education on AWS. ● Includes ready-made, purpose-built models as AI services and proven methods to adopt MLOps techniques. DESCRIPTION Using machine learning and artificial intelligence (AI) in existing business processes has been successful. Even AWS's ML and AI services make it simple and economical to conduct machine learning experiments. This book will show readers how to use the complete set of AI and ML services available on AWS to streamline the management of their whole AI operation and speed up their innovation. In this book, you'll learn how to build data lakes, build and train machine learning models, automate MLOps, ensure maximum data reusability and reproducibility, and much more. The applications presented in the book show how to make the most of several different AWS offerings, including Amazon Comprehend, Amazon Rekognition, Amazon Lookout, and AutoML. This book teaches you to manage massive data lakes, train artificial intelligence models, release these applications into production, and track their progress in real-time. You will learn how to use the pre-trained models for various tasks, including picture recognition, automated data extraction, image/video detection, and anomaly detection. Every step of your Machine Learning and AI project's development process is optimised throughout the book by utilising Amazon's pre-made, purpose-built AI services. WHAT YOU WILL LEARN ● Learn how to build, deploy, and manage large-scale AI and ML applications on AWS. ● Get your hands dirty with AWS AI services like SageMaker, Comprehend, Rekognition, Lookout, and AutoML. ● Master data transformation, feature engineering, and model training with Amazon SageMaker modules. ● Use neural networks, distributed learning, and deep learning algorithms to improve ML models. ● Use AutoML, SageMaker Canvas, and Autopilot for Model Deployment and Evaluation. ● Acquire expertise with Amazon SageMaker Studio, Jupyter Server, and ML frameworks such as TensorFlow and MXNet. WHO THIS BOOK IS FOR Data Engineers, Data Scientists, AWS and Cloud Professionals who are comfortable with machine learning and the fundamentals of Python will find this book powerful. Familiarity with AWS would be helpful but is not required. TABLE OF CONTENTS 1. Introducing the ML Workflow 2. Hydrating the Data Lake 3. Predicting the Future With Features 4. Orchestrating the Data Continuum 5. Casting a Deeper Net (Algorithms and Neural Networks) 6. Iteration Makes Intelligence (Model Training and Tuning) 7. Let George Take Over (AutoML in Action) 8. Blue or Green (Model Deployment Strategies) 9. Wisdom at Scale with Elastic Inference 10. Adding Intelligence with Sensory Cognition 11. AI for Industrial Automation 12. Operationalized Model Assembly (MLOps and Best Practices)

Hands-On Artificial Intelligence on Amazon Web Services

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Release : 2019-10-04
Genre : Computers
Kind : eBook
Book Rating : 470/5 ( reviews)

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Book Synopsis Hands-On Artificial Intelligence on Amazon Web Services by : Subhashini Tripuraneni

Download or read book Hands-On Artificial Intelligence on Amazon Web Services written by Subhashini Tripuraneni. This book was released on 2019-10-04. Available in PDF, EPUB and Kindle. Book excerpt: Perform cloud-based machine learning and deep learning using Amazon Web Services such as SageMaker, Lex, Comprehend, Translate, and Polly Key FeaturesExplore popular machine learning and deep learning services with their underlying algorithmsDiscover readily available artificial intelligence(AI) APIs on AWS like Vision and Language ServicesDesign robust architectures to enable experimentation, extensibility, and maintainability of AI appsBook Description From data wrangling through to translating text, you can accomplish this and more with the artificial intelligence and machine learning services available on AWS. With this book, you’ll work through hands-on exercises and learn to use these services to solve real-world problems. You’ll even design, develop, monitor, and maintain machine and deep learning models on AWS. The book starts with an introduction to AI and its applications in different industries, along with an overview of AWS artificial intelligence and machine learning services. You’ll then get to grips with detecting and translating text with Amazon Rekognition and Amazon Translate. The book will assist you in performing speech-to-text with Amazon Transcribe and Amazon Polly. Later, you’ll discover the use of Amazon Comprehend for extracting information from text, and Amazon Lex for building voice chatbots. You will also understand the key capabilities of Amazon SageMaker such as wrangling big data, discovering topics in text collections, and classifying images. Finally, you’ll cover sales forecasting with deep learning and autoregression, before exploring the importance of a feedback loop in machine learning. By the end of this book, you will have the skills you need to implement AI in AWS through hands-on exercises that cover all aspects of the ML model life cycle. What you will learnGain useful insights into different machine and deep learning modelsBuild and deploy robust deep learning systems to productionTrain machine and deep learning models with diverse infrastructure specificationsScale AI apps without dealing with the complexity of managing the underlying infrastructureMonitor and Manage AI experiments efficientlyCreate AI apps using AWS pre-trained AI servicesWho this book is for This book is for data scientists, machine learning developers, deep learning researchers, and artificial intelligence enthusiasts who want to harness the power of AWS to implement powerful artificial intelligence solutions. A basic understanding of machine learning concepts is expected.

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