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Ultimate Generative AI Solutions on Google Cloud - Practical Strategies for Building and Scaling Generative AI Solutions with Google Cloud Tools Langchain RAG and LLMOps - cover

Ultimate Generative AI Solutions on Google Cloud - Practical Strategies for Building and Scaling Generative AI Solutions with Google Cloud Tools Langchain RAG and LLMOps

Arun Pandey

Editorial: Orange Education Pvt Ltd

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Sinopsis

Unlock Generative AI's Potential: Transform Ideas into Reality on Google Cloud!Key Features● Step-by-step guidance for building Generative AI apps on Google Cloud Platform.● Pro tips for fine-tuning models to achieve optimal performance.● Industry-specific use cases for practical, hands-on learning.Book DescriptionGenerative AI, powered by Google Cloud Platform (GCP), is reshaping industries with its advanced capabilities in automating and enhancing complex tasks. The Ultimate Generative AI Solutions on Google Cloud is your comprehensive guide to harnessing this powerful combination to innovate and excel in your job role. It explores foundational machine learning concepts and dives deep into Generative AI, providing the essential knowledge needed to conceptualize, develop, and deploy cutting-edge AI solutions.Within these pages, you'll explore Large Language Models (LLMs), Prompt engineering, Fine-tuning techniques, and the latest advancements in AI, with special emphasis on Parameter-Efficient Fine-Tuning (PEFT) and Reinforcement Learning with Human Feedback (RLHF). You'll also learn about the integration of LangChain and Retrieval-Augmented Generation (RAG) to enhance AI capabilities. By mastering these techniques, you can optimize model performance while conserving resources. The integration of GCP services simplifies the development process, enabling the creation of robust AI applications with ease.By the end of this book, you will not only understand the technical aspects of Generative AI but also gain practical skills that can transform your work to drive innovation and boost operational efficiency with Generative AI on GCP.What you will learn● Build and deploy cutting-edge generative AI solutions using Google Cloud, LangChain, and RAG.● Fine-tune large language models (LLMs) with PEFT to meet precise business objectives.● Master prompt engineering techniques to enhance model performance with GCP tools.● Optimize production AI for efficiency and scalability using GCP’s Cloud Functions and Cloud Run.● Apply real-world industry use cases to drive innovation and solve complex problems with LLMOps.● Manage and streamline AI projects effectively using GCP services like Dataflow, Pub/Sub, and Monitoring.Table of Contents1. Generative AI Essentials2. Google Cloud Basics3. Getting Started with Large Language Models4. Prompt Engineering and Contextual Learning5. Fine-Tuning a Large Language Model6. Parameter-Efficient Fine-Tuning (PEFT)7. Reinforcement Learning with Human Feedback8. Model Optimization9. LLMOps for Managing and Monitoring AI Projects10. Harnessing RAG and LangChain11. Case Studies and Real-World Implementations       IndexAbout the AuthorsArun Pandey is a distinguished technology leader and AI innovator with over 20 years of experience in the f ields of Generative AI, deep learning, and enterprise solutions. As a serial entrepreneur and co-founder of multiple AI startups, he has made significant contributions to the industry, earning recognition as a top global AI influencer and an award-winning author.Arun's extensive background includes leading high-performing teams in Fortune 500 companies, where he generated over USD 3 billion in revenue through innovative technology solutions. His passion for knowledge and commitment to sharing insights have culminated in this book, aimed at empowering readers to harness the power of Generative AI on Google Cloud.In addition to his professional achievements, Arun is dedicated to fostering a community of learners and practitioners in AI, inspired by his mentors and the incredible journey that has shaped his career.
Disponible desde: 29/12/2024.
Longitud de impresión: 334 páginas.

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