Ai Unleashed A Holistic Guide To Mastering Artificial Intelligence
Download Ai Unleashed A Holistic Guide To Mastering Artificial Intelligence PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Ai Unleashed A Holistic Guide To Mastering Artificial Intelligence book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
AI Unleashed: A Holistic Guide to Mastering Artificial Intelligence
Embark on a transformative journey through the realm of artificial intelligence with "AI Unleashed: A Holistic Guide to Mastering Artificial Intelligence." In this comprehensive and unique guide, you'll uncover the depths of AI's complexities, from foundational concepts to cutting-edge techniques that are shaping the future. From the evolution of AI's journey from fiction to reality, to the powerful insights of unsupervised learning, deep learning, and reinforcement learning, this book equips you with the knowledge to unravel AI's intricacies. Through vivid explanations, real-world examples, and immersive chapters, you'll traverse the landscape of supervised and unsupervised learning, delve into neural networks and advanced algorithms, and comprehend the ethical considerations that underpin responsible AI development. But "AI Unleashed" doesn't stop at theory—it propels you into action. You'll discover the practical aspects of data preprocessing, model tuning, and deployment strategies that are pivotal for creating AI solutions that work seamlessly in the real world. Moreover, you'll explore the intersections of AI with diverse industries, from healthcare and finance to quantum computing, positioning you at the forefront of innovation. As you journey through these pages, you'll not only gain a deep understanding of AI's intricacies but also develop the skills to build intelligent systems that create positive impacts. Whether you're a seasoned AI practitioner or a curious beginner, "AI Unleashed" empowers you to unlock the boundless potential of artificial intelligence and embark on a path of continuous learning that propels you forward in the dynamic world of AI innovation.
Mastering Large Language Models with Python: Unleash the Power of Advanced Natural Language Processing for Enterprise Innovation and Efficiency Using Large Language Models (LLMs) with Python
Author: Raj Arun
language: en
Publisher: Orange Education Pvt Limited
Release Date: 2024-04-12
A Comprehensive Guide to Leverage Generative AI in the Modern Enterprise Key Features● Gain a comprehensive understanding of LLMs within the framework of Generative AI, from foundational concepts to advanced applications. ● Dive into practical exercises and real-world applications, accompanied by detailed code walkthroughs in Python. ● Explore LLMOps with a dedicated focus on ensuring trustworthy AI and best practices for deploying, managing, and maintaining LLMs in enterprise settings. Book Description “Mastering Large Language Models with Python” is an indispensable resource that offers a comprehensive exploration of Large Language Models (LLMs), providing the essential knowledge to leverage these transformative AI models effectively. From unraveling the intricacies of LLM architecture to practical applications like code generation and AI-driven recommendation systems, readers will gain valuable insights into implementing LLMs in diverse projects. Covering both open-source and proprietary LLMs, the book delves into foundational concepts and advanced techniques, empowering professionals to harness the full potential of these models. Detailed discussions on quantization techniques for efficient deployment, operational strategies with LLMOps, and ethical considerations ensure a well-rounded understanding of LLM implementation. Through real-world case studies, code snippets, and practical examples, readers will navigate the complexities of LLMs with confidence, paving the way for innovative solutions and organizational growth. Whether you seek to deepen your understanding, drive impactful applications, or lead AI-driven initiatives, this book equips you with the tools and insights needed to excel in the dynamic landscape of artificial intelligence. What you will learn ● In-depth study of LLM architecture and its versatile applications across industries. ● Harness open-source and proprietary LLMs to craft innovative solutions. ● Implement LLM APIs for a wide range of tasks spanning natural language processing, audio analysis, and visual recognition. ● Optimize LLM deployment through techniques such as quantization and operational strategies like LLMOps, ensuring efficient and scalable model usage. Table of Contents 1. The Basics of Large Language Models and Their Applications 2. Demystifying Open-Source Large Language Models 3. Closed-Source Large Language Models 4. LLM APIs for Various Large Language Model Tasks 5. Integrating Cohere API in Google Sheets 6. Dynamic Movie Recommendation Engine Using LLMs 7. Document-and Web-based QA Bots with Large Language Models 8. LLM Quantization Techniques and Implementation 9. Fine-tuning and Evaluation of LLMs 10. Recipes for Fine-Tuning and Evaluating LLMs 11. LLMOps - Operationalizing LLMs at Scale 12. Implementing LLMOps in Practice Using MLflow on Databricks 13. Mastering the Art of Prompt Engineering 14. Prompt Engineering Essentials and Design Patterns 15. Ethical Considerations and Regulatory Frameworks for LLMs 16. Towards Trustworthy Generative AI (A Novel Framework Inspired by Symbolic Reasoning) Index
Strengthening Deep Neural Networks
As deep neural networks (DNNs) become increasingly common in real-world applications, the potential to deliberately "fool" them with data that wouldn’t trick a human presents a new attack vector. This practical book examines real-world scenarios where DNNs—the algorithms intrinsic to much of AI—are used daily to process image, audio, and video data. Author Katy Warr considers attack motivations, the risks posed by this adversarial input, and methods for increasing AI robustness to these attacks. If you’re a data scientist developing DNN algorithms, a security architect interested in how to make AI systems more resilient to attack, or someone fascinated by the differences between artificial and biological perception, this book is for you. Delve into DNNs and discover how they could be tricked by adversarial input Investigate methods used to generate adversarial input capable of fooling DNNs Explore real-world scenarios and model the adversarial threat Evaluate neural network robustness; learn methods to increase resilience of AI systems to adversarial data Examine some ways in which AI might become better at mimicking human perception in years to come