Applied Generative AI for Beginners

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Author :
Publisher : Apress
ISBN 13 : 9781484299937
Total Pages : 0 pages
Book Rating : 4.2/5 (999 download)

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Book Synopsis Applied Generative AI for Beginners by : Akshay Kulkarni

Download or read book Applied Generative AI for Beginners written by Akshay Kulkarni and published by Apress. This book was released on 2023-12-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a deep dive into the world of generative AI, covering everything from the basics of neural networks to the intricacies of large language models like ChatGPT and Google Bard. It serves as a one-stop resource for anyone interested in understanding and applying this transformative technology and is particularly aimed at those just getting started with generative AI. Applied Generative AI for Beginners is structured around detailed chapters that will guide you from foundational knowledge to practical implementation. It starts with an introduction to generative AI and its current landscape, followed by an exploration of how the evolution of neural networks led to the development of large language models. The book then delves into specific architectures like ChatGPT and Google Bard, offering hands-on demonstrations for implementation using tools like Sklearn. You’ll also gain insight into the strategic aspects of implementing generative AI in an enterprise setting, with the authors covering crucial topics such as LLMOps, technology stack selection, and in-context learning. The latter part of the book explores generative AI for images and provides industry-specific use cases, making it a comprehensive guide for practical application in various domains. Whether you're a data scientist looking to implement advanced models, a business leader aiming to leverage AI for enterprise growth, or an academic interested in cutting-edge advancements, this book offers a concise yet thorough guide to mastering generative AI, balancing theoretical knowledge with practical insights. What You Will Learn Gain a solid understanding of generative AI, starting from the basics of neural networks and progressing to complex architectures like ChatGPT and Google Bard Implement large language models using Sklearn, complete with code examples and best practices for real-world application Learn how to integrate LLM’s in enterprises, including aspects like LLMOps and technology stack selection Understand how generative AI can be applied across various industries, from healthcare and marketing to legal compliance through detailed use cases and actionable insights Who This Book Is For Data scientists, AI practitioners, Researchers and software engineers interested in generative AI and LLMs.

Generative Deep Learning

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Author :
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492041890
Total Pages : 360 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Generative Deep Learning by : David Foster

Download or read book Generative Deep Learning written by David Foster and published by "O'Reilly Media, Inc.". This book was released on 2019-06-28 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative modeling is one of the hottest topics in AI. It’s now possible to teach a machine to excel at human endeavors such as painting, writing, and composing music. With this practical book, machine-learning engineers and data scientists will discover how to re-create some of the most impressive examples of generative deep learning models, such as variational autoencoders,generative adversarial networks (GANs), encoder-decoder models and world models. Author David Foster demonstrates the inner workings of each technique, starting with the basics of deep learning before advancing to some of the most cutting-edge algorithms in the field. Through tips and tricks, you’ll understand how to make your models learn more efficiently and become more creative. Discover how variational autoencoders can change facial expressions in photos Build practical GAN examples from scratch, including CycleGAN for style transfer and MuseGAN for music generation Create recurrent generative models for text generation and learn how to improve the models using attention Understand how generative models can help agents to accomplish tasks within a reinforcement learning setting Explore the architecture of the Transformer (BERT, GPT-2) and image generation models such as ProGAN and StyleGAN

Generative AI from Beginner to Paid Professional, Part 1

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Author :
Publisher : AB Publisher LLC
ISBN 13 :
Total Pages : 43 pages
Book Rating : 4./5 ( download)

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Book Synopsis Generative AI from Beginner to Paid Professional, Part 1 by : Bolakale Aremu

Download or read book Generative AI from Beginner to Paid Professional, Part 1 written by Bolakale Aremu and published by AB Publisher LLC. This book was released on 2024-10-01 with total page 43 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the Power of Generative AI and Accelerate Your Journey from Beginner to Paid Professional. Are you eager to break into the world of Generative AI but unsure where to start? This step-by-step series is designed for anyone looking to quickly grasp the fundamentals of AI and harness its potential to enhance their skills, grow their career, and start monetizing their expertise. In Part 1 of this essential series, you’ll dive into the basics of Generative AI, discovering how powerful tools from Google and other major platforms can transform your workflow, ignite your creativity, and open new career opportunities. Written in an easy-to-digest microlearning format, this guide simplifies complex AI concepts, ensuring you gain practical skills from day one. What You’ll Learn: Generative AI Essentials: Master the foundations of AI technology and how it’s revolutionizing industries worldwide. Google Tools for AI: Explore Google’s suite of AI-powered tools and learn how to integrate them into your projects. Real-World Applications: Get hands-on experience with actionable examples and projects designed to elevate your understanding. This series goes beyond theory because it takes you on a progressive journey from foundational knowledge to advanced skills needed to become a professional in the rapidly growing AI field. What’s Next in the Series? After establishing a solid base in Part 1, you’ll advance to topics like: LangChain & Hugging Face API: Unlock more powerful tools for building AI models and applications. Gemini Pro LLM Models & Vector Databases: Learn to work with cutting-edge language models and efficient data handling systems. Llama Index & AI Deployment Projects: Gain the skills to deploy AI projects in real-world environments, ready to impress clients or employers. Whether you’re a student, freelancer, or professional looking to boost your expertise, this book series will guide you every step of the way, turning you into a confident AI professional ready to meet the demands of a rapidly evolving market.

Basics of Linear Algebra for Machine Learning

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Author :
Publisher : Machine Learning Mastery
ISBN 13 :
Total Pages : 211 pages
Book Rating : 4./5 ( download)

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Book Synopsis Basics of Linear Algebra for Machine Learning by : Jason Brownlee

Download or read book Basics of Linear Algebra for Machine Learning written by Jason Brownlee and published by Machine Learning Mastery. This book was released on 2018-01-24 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear algebra is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. In this laser-focused Ebook, you will finally cut through the equations, Greek letters, and confusion, and discover the topics in linear algebra that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover what linear algebra is, the importance of linear algebra to machine learning, vector, and matrix operations, matrix factorization, principal component analysis, and much more.

Deep Learning for Coders with fastai and PyTorch

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Publisher : O'Reilly Media
ISBN 13 : 1492045497
Total Pages : 624 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Deep Learning for Coders with fastai and PyTorch by : Jeremy Howard

Download or read book Deep Learning for Coders with fastai and PyTorch written by Jeremy Howard and published by O'Reilly Media. This book was released on 2020-06-29 with total page 624 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Applied Artificial Intelligence

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Publisher :
ISBN 13 : 9780998289021
Total Pages : 246 pages
Book Rating : 4.2/5 (89 download)

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Book Synopsis Applied Artificial Intelligence by : Mariya Yao

Download or read book Applied Artificial Intelligence written by Mariya Yao and published by . This book was released on 2018-04-30 with total page 246 pages. Available in PDF, EPUB and Kindle. Book excerpt: This bestselling book gives business leaders and executives a foundational education on how to leverage artificial intelligence and machine learning solutions to deliver ROI for your business.

AI for Beginners

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Author :
Publisher : Independently Published
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.8/5 (848 download)

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Book Synopsis AI for Beginners by : Alan Miller

Download or read book AI for Beginners written by Alan Miller and published by Independently Published. This book was released on 2024-03-24 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: GET YOU BONUS: MASTERING GBT'S: A guide within a guide where we delve into practical tips and advanced techniques to ensure you get the most out of ChatGPT. Are you intrigued by the power of ai? Do you wonder how machines learn to generate content that feels uniquely human? Are you looking to deepen your understanding in the evolving field of generative ai? "AI FOR BEGINNERS is your essential resource into the world of artificial intelligence. This book demystifies the complex concepts of Generative AI, making them accessible to anyone with curiosity and a desire to explore the future of creativity and innovation. Within these pages, you'll discover: An In-Depth Exploration of AI and Generative AI: Gain a comprehensive understanding of the fundamentals and the core technologies and theories that enable the magic of Generative AI. Practical Applications: Discover the transformative impact of Generative AI across art, music, video production, data analysis, coding and beyond. Hands-On Guidance: This book not only teaches you how AI works but also how to apply it effectively, offering practical advice and step by step guidance for leveraging Generative AI in your life and projects. Ethical Insights: Learn about the responsible use of AI, addressing the moral implications of AI-generated content and its influence on our digital landscape. Whether you're an aspiring developer, an artist intrigued by the possibilities of AI, or simply someone fascinated by the capability of technology to emulate and augment human creativity, this book offers a comprehensive and insightful exploration of Generative AI. This book is not just a guide; it's a gateway to the future. Are you ready to transform curiosity into comprehensive knowledge and ideas into tangible outcomes? Grab you copy and begin your journey!

Artificial Intelligence with Python

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Author :
Publisher : Packt Publishing Ltd
ISBN 13 : 1786469677
Total Pages : 437 pages
Book Rating : 4.7/5 (864 download)

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Book Synopsis Artificial Intelligence with Python by : Prateek Joshi

Download or read book Artificial Intelligence with Python written by Prateek Joshi and published by Packt Publishing Ltd. This book was released on 2017-01-27 with total page 437 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.

Generative AI with Tensor Flow

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Author :
Publisher : Anand Vemula
ISBN 13 :
Total Pages : 71 pages
Book Rating : 4./5 ( download)

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Book Synopsis Generative AI with Tensor Flow by : Anand Vemula

Download or read book Generative AI with Tensor Flow written by Anand Vemula and published by Anand Vemula. This book was released on with total page 71 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Exploring Generative AI: From Fundamentals to Applications" is a comprehensive guide to understanding and applying generative artificial intelligence (AI). The book is divided into five parts, each covering essential aspects of generative AI, from foundational concepts to advanced techniques, practical applications, and future directions. In Part I, "Introduction to Generative AI," readers are introduced to the fundamental concepts of generative models, TensorFlow, and setting up a development environment. This section lays the groundwork for understanding how generative AI works and provides the necessary tools for experimentation. Part II, "Fundamentals of Generative Models," explores key techniques such as autoencoders, variational autoencoders (VAEs), generative adversarial networks (GANs), and conditional GANs. Each chapter provides in-depth explanations of the architecture, training methods, and real-world applications of these models. In Part III, "Advanced Topics in Generative AI," readers dive deeper into advanced techniques such as deep convolutional GANs (DCGANs), StyleGAN, recurrent neural networks (RNNs) for generative sequences, and reinforcement learning for generative AI. These chapters explore cutting-edge research and developments in the field, providing insights into the latest advancements and future trends. Part IV, "Applications of Generative AI," showcases the diverse applications of generative AI across various domains, including image generation and manipulation, text generation, music generation, and healthcare. Readers learn how generative models are being used to solve real-world problems and drive innovation in fields such as healthcare, entertainment, and creative industries. Finally, in Part V, "Future Directions and Ethical Considerations," the book examines emerging trends in generative AI and addresses ethical considerations and challenges associated with the technology. Readers gain insights into the potential societal impacts of generative AI and the importance of responsible AI development and governance. "Exploring Generative AI: From Fundamentals to Applications" is a valuable resource for students, researchers, and practitioners interested in understanding and leveraging the power of generative AI to drive innovation and address complex challenges in today's rapidly evolving world.

Generative AI for Transformational Management

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Author :
Publisher : IGI Global
ISBN 13 :
Total Pages : 418 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Generative AI for Transformational Management by : Gomathi Sankar, Jeganathan

Download or read book Generative AI for Transformational Management written by Gomathi Sankar, Jeganathan and published by IGI Global. This book was released on 2024-08-27 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: The business world today is changing at a breakneck pace. Traditional management practices need help keeping up with the uncertainties and complexities of the digital age. Leaders face a lot of pressure to innovate, adapt, and drive transformative change within their organizations. However, they need more than just conventional wisdom to navigate this terrain. A deep understanding of emerging technologies like artificial intelligence (AI) and their practical applications in management is essential. Generative AI for Transformational Management offers a compelling solution to these challenges. This book provides a roadmap for leveraging AI to drive organizational transformation by exploring the intersection of generative AI and visionary leadership. By examining real-world case studies and practical applications, readers can learn how AI can be integrated into leadership practices to promote innovation and proactive decision-making and effectively navigate the complexities of the digital age.

Introduction to Generative AI

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Author :
Publisher : Simon and Schuster
ISBN 13 : 1633437191
Total Pages : 334 pages
Book Rating : 4.6/5 (334 download)

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Book Synopsis Introduction to Generative AI by : Numa Dhamani

Download or read book Introduction to Generative AI written by Numa Dhamani and published by Simon and Schuster. This book was released on 2024-02-27 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI tools like ChatGPT are amazing—but how will their use impact our society? This book introduces the world-transforming technology and the strategies you need to use generative AI safely and effectively. Introduction to Generative AI gives you the hows-and-whys of generative AI in accessible language. In this easy-to-read introduction, you’ll learn: How large language models (LLMs) work How to integrate generative AI into your personal and professional workflows Balancing innovation and responsibility The social, legal, and policy landscape around generative AI Societal impacts of generative AI Where AI is going Anyone who uses ChatGPT for even a few minutes can tell that it’s truly different from other chatbots or question-and-answer tools. Introduction to Generative AI guides you from that first eye-opening interaction to how these powerful tools can transform your personal and professional life. In it, you’ll get no-nonsense guidance on generative AI fundamentals to help you understand what these models are (and aren’t) capable of, and how you can use them to your greatest advantage. Foreword by Sahar Massachi. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Generative AI tools like ChatGPT, Bing, and Bard have permanently transformed the way we work, learn, and communicate. This delightful book shows you exactly how Generative AI works in plain, jargon-free English, along with the insights you’ll need to use it safely and effectively. About the book Introduction to Generative AI guides you through benefits, risks, and limitations of Generative AI technology. You’ll discover how AI models learn and think, explore best practices for creating text and graphics, and consider the impact of AI on society, the economy, and the law. Along the way, you’ll practice strategies for getting accurate responses and even understand how to handle misuse and security threats. What's inside How large language models work Integrate Generative AI into your daily work Balance innovation and responsibility About the reader For anyone interested in Generative AI. No technical experience required. About the author Numa Dhamani is a natural language processing expert working at the intersection of technology and society. Maggie Engler is an engineer and researcher currently working on safety for large language models. The technical editor on this book was Maris Sekar. Table of Contents 1 Large language models: The power of AI Evolution of natural language processing 2 Training large language models 3 Data privacy and safety with LLMs 4 The evolution of created content 5 Misuse and adversarial attacks 6 Accelerating productivity: Machine-augmented work 7 Making social connections with chatbots 8 What’s next for AI and LLMs 9 Broadening the horizon: Exploratory topics in AI

Machine Learning For Dummies

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Author :
Publisher : John Wiley & Sons
ISBN 13 : 1119724015
Total Pages : 471 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning For Dummies by : John Paul Mueller

Download or read book Machine Learning For Dummies written by John Paul Mueller and published by John Wiley & Sons. This book was released on 2021-02-09 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: One of Mark Cuban’s top reads for better understanding A.I. (inc.com, 2021) Your comprehensive entry-level guide to machine learning While machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie Ex Machina—it is a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit-scoring, building accurate and sophisticated pricing models—and way, way more. Unlike most machine learning books, the fully updated 2nd Edition of Machine Learning For Dummies doesn't assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don't need to be a math whiz to build fun new tools and apply them to your work and study. Understand the history of AI and machine learning Work with Python 3.8 and TensorFlow 2.x (and R as a download) Build and test your own models Use the latest datasets, rather than the worn out data found in other books Apply machine learning to real problems Whether you want to learn for college or to enhance your business or career performance, this friendly beginner's guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that's impacting lives for the better all over the world.

General Aspects of Applying Generative AI in Higher Education

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Author :
Publisher : Springer Nature
ISBN 13 : 3031656911
Total Pages : 440 pages
Book Rating : 4.0/5 (316 download)

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Book Synopsis General Aspects of Applying Generative AI in Higher Education by : Mohamed Lahby

Download or read book General Aspects of Applying Generative AI in Higher Education written by Mohamed Lahby and published by Springer Nature. This book was released on with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt:

INSIDE GENERATIVE AI

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Author :
Publisher : Rick Spair
ISBN 13 :
Total Pages : 146 pages
Book Rating : 4./5 ( download)

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Book Synopsis INSIDE GENERATIVE AI by : Rick Spair

Download or read book INSIDE GENERATIVE AI written by Rick Spair and published by Rick Spair. This book was released on with total page 146 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI represents a groundbreaking frontier in the realm of artificial intelligence, where machines not only learn from data but also create new data, mimicking the inventive processes of human creativity. This book is a comprehensive guide that explores the depths of generative AI, from foundational concepts to advanced applications, and provides a rich array of hands-on projects and real-world case studies. Why Generative AI? In recent years, generative AI has transformed from a niche area of research to a central pillar of AI innovation, with profound implications for various industries. From generating realistic images and videos to composing music and writing compelling narratives, generative AI models are pushing the boundaries of what machines can do. This evolution has not only expanded the capabilities of AI but also sparked new forms of creative expression and problem-solving. Generative AI's impact is evident in numerous fields: Art and Design: Artists and designers are leveraging AI to create stunning visual artworks, intricate designs, and immersive digital environments. Tools like DeepDream and GauGAN have opened new horizons in artistic creativity, enabling the generation of unique and surreal visuals. Media and Entertainment: The media industry is using generative AI to automate content creation, from news articles to movie scripts, and even to generate entire virtual worlds for video games and virtual reality experiences. AI-generated music and soundtracks are also becoming increasingly popular, offering new ways to enhance auditory experiences. Healthcare: In healthcare, generative AI is aiding in the discovery of new drugs, personalizing treatment plans, and enhancing medical imaging. By generating realistic simulations and models, AI helps researchers and practitioners explore new avenues in medical science. Business and Marketing: Businesses are employing generative AI to create personalized marketing content, design products, and optimize supply chains. AI-driven tools are enabling companies to innovate faster and more efficiently, providing a competitive edge in the market. Dive into the projects, experiment with different models, and engage with the AI community. By learning, creating, and sharing, you become a part of the vibrant and dynamic landscape of generative AI. The future is filled with opportunities, and this book is your gateway to exploring and contributing to the exciting world of generative AI. Welcome to the journey!

Data Science Solutions on Azure

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Author :
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.8/5 (688 download)

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Book Synopsis Data Science Solutions on Azure by : JULIAN. SINGH SOH (PRIYANSHI.)

Download or read book Data Science Solutions on Azure written by JULIAN. SINGH SOH (PRIYANSHI.) and published by . This book was released on 2024-10-26 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This revamped and updated book focuses on the latest in AI technology--Generative AI. It builds on the first edition by moving away from traditional data science into the area of applied AI using the latest breakthroughs in Generative AI. Based on real-world projects, this edition takes a deep look into new concepts and approaches such as Prompt Engineering, testing and grounding of Large Language Models, fine tuning, and implementing new solution architectures such as Retrieval Augmented Generation (RAG). You will learn about new embedded AI technologies in Search, such as Semantic and Vector Search. Written with a view on how to implement Generative AI in software, this book contains examples and sample code. In addition to traditional Data Science experimentation in Azure Machine Learning (AML) that was covered in the first edition, the authors cover new tools such as Azure AI Studio, specifically for testing and experimentation with Generative AI models. What's New in this Book Provides new concepts, tools, and technologies such as Large and Small Language Models, Semantic Kernel, and Automatic Function Calling Takes a deeper dive into using Azure AI Studio for RAG and Prompt Engineering design Includes new and updated case studies for Azure OpenAI Teaches about Copilots, plugins, and agents What You'll Learn Get up to date on the important technical aspects of Large Language Models, based on Azure OpenAI as the reference platform Know about the different types of models: GPT3.5 Turbo, GPT4, GPT4o, Codex, DALL-E, and Small Language Models such as Phi-3 Develop new skills such as Prompt Engineering and fine tuning of Large/Small Language Models Understand and implement new architectures such as RAG and Automatic Function Calling Understand approaches for implementing Generative AI using LangChain and Semantic Kernel See how real-world projects help you identify great candidates for Applied AI projects, including Large/Small Language Models Who This Book Is For Software engineers and architects looking to deploy end-to-end Generative AI solutions on Azure with the latest tools and techniques.

Generative AI For Beginners Playbook

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Author :
Publisher :
ISBN 13 : 9781988099187
Total Pages : 0 pages
Book Rating : 4.0/5 (991 download)

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Book Synopsis Generative AI For Beginners Playbook by : Branson Adams

Download or read book Generative AI For Beginners Playbook written by Branson Adams and published by . This book was released on 2024-06-05 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Artificial Intelligence in Finance

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Author :
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1492055387
Total Pages : 478 pages
Book Rating : 4.4/5 (92 download)

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Book Synopsis Artificial Intelligence in Finance by : Yves Hilpisch

Download or read book Artificial Intelligence in Finance written by Yves Hilpisch and published by "O'Reilly Media, Inc.". This book was released on 2020-10-14 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: The widespread adoption of AI and machine learning is revolutionizing many industries today. Once these technologies are combined with the programmatic availability of historical and real-time financial data, the financial industry will also change fundamentally. With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading. Author Yves Hilpisch shows practitioners, students, and academics in both finance and data science practical ways to apply machine learning and deep learning algorithms to finance. Thanks to lots of self-contained Python examples, you'll be able to replicate all results and figures presented in the book. In five parts, this guide helps you: Learn central notions and algorithms from AI, including recent breakthroughs on the way to artificial general intelligence (AGI) and superintelligence (SI) Understand why data-driven finance, AI, and machine learning will have a lasting impact on financial theory and practice Apply neural networks and reinforcement learning to discover statistical inefficiencies in financial markets Identify and exploit economic inefficiencies through backtesting and algorithmic trading--the automated execution of trading strategies Understand how AI will influence the competitive dynamics in the financial industry and what the potential emergence of a financial singularity might bring about