Generative Ai An Overview
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Generative Ai An Overview
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Author :
language : en
Publisher: Editor IJSMI
Release Date : 2025-06-19
Generative Ai An Overview written by and has been published by Editor IJSMI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-19 with Computers categories.
Generative Artificial Intelligence, an Artificial Intelligence concept which is used to create own data which includes creating text, audio, video, images, programming codes and also advanced data structures such as protein structures. Before the Generative AI, Artificial Intelligence models used Machine learning models to predict pattern and structures. Generative AI models are widely being used in Business, healthcare, education and media sectors. Generative AI helps organizations to be more innovative, cost effective and efficient in their operations. Machine learning, Deep Learning, Large Language Models, transformers forms the basis for creating own data in Generative AI environment. Generative AI or Gen AI uses large data set to frame set of rules which is used in creating of new content. ChatGPT and Microsoft Copilot are one of the examples of the Generative AI tools which helps user to create texts and develop answers to users questions. Both proprietary as well as open source Generative aI models are available now. Large Language Models or foundation models which are training large datasets forms the basis of creating contents in Generative AI. These models do not need to be trained and their trained on their own and this is the major difference between supervised Machine learning models which require labeling for classifying the data. Generative AI model building starts with the data collection and processing of large datasets, then moving to model building, training and pattern learning from those large datasets and then finally rendering and validating different created the different types of contents such as text, audio, video and images. The book also provides overview of Python programming for the readers who are first time learners of Python programming. The contents are adopted from Author’s book on Python programming for Data Scientists
Generative Ai An Overview
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Author : Editor Ijsmi
language : en
Publisher: Independently Published
Release Date : 2025-06-19
Generative Ai An Overview written by Editor Ijsmi and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-19 with Computers categories.
Generative Artificial Intelligence, an Artificial Intelligence concept which is used to create own data which includes creating text, audio, video, images, programming codes and also advanced data structures such as protein structures. Before the Generative AI, Artificial Intelligence models used Machine learning models to predict pattern and structures. Generative AI models are widely being used in Business, healthcare, education and media sectors. Generative AI helps organizations to be more innovative, cost effective and efficient in their operations. Machine learning, Deep Learning, Large Language Models, transformers forms the basis for creating own data in Generative AI environment. Generative AI or Gen AI uses large data set to frame set of rules which is used in creating of new content. ChatGPT and Microsoft Copilot are one of the examples of the Generative AI tools which helps user to create texts and develop answers to users questions. Both proprietary as well as open source Generative aI models are available now. Large Language Models or foundation models which are training large datasets forms the basis of creating contents in Generative AI. These models do not need to be trained and their trained on their own and this is the major difference between supervised Machine learning models which require labeling for classifying the data. Generative AI model building starts with the data collection and processing of large datasets, then moving to model building, training and pattern learning from those large datasets and then finally rendering and validating different created the different types of contents such as text, audio, video and images. The book also provides overview of Python programming for the readers who are first time learners of Python programming. The contents are adopted from Author's book on Python programming for Data Scientists
Generative Ai And Large Language Models
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Author : Aditya Pratap Bhuyan
language : en
Publisher: Aditya Pratap Bhuyan
Release Date : 2024-07-24
Generative Ai And Large Language Models written by Aditya Pratap Bhuyan and has been published by Aditya Pratap Bhuyan this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Computers categories.
Artificial Intelligence is reshaping our world, and at the forefront of this revolution are Generative AI and Large Language Models (LLMs). This book, "Generative AI and Large Language Models: Revolutionizing the Future," offers an in-depth exploration of these groundbreaking technologies, delving into their foundations, development, and profound implications for various industries and society as a whole. Starting with a historical overview of AI, the book traces the evolution of machine learning and deep learning, setting the stage for understanding the rise of generative AI. Readers will discover the inner workings of LLMs, from their advanced neural network architectures to the massive datasets and computational power required for their training. Key models, such as the Generative Pre-trained Transformer (GPT) series, are examined in detail, showcasing their remarkable capabilities in natural language processing and beyond. The book also addresses the ethical and social challenges posed by these powerful technologies. Issues such as bias, fairness, and privacy are discussed, alongside the need for transparent and accountable AI systems. Through real-world applications and case studies, readers will see how generative AI is transforming fields like healthcare, finance, content creation, and more. Looking ahead, the book explores future trends and innovations, highlighting potential advancements and the ongoing research aimed at enhancing AI's efficiency and multimodal capabilities. It envisions a future where AI and humans collaborate more closely, driving progress and innovation across all domains. "Generative AI and Large Language Models: Revolutionizing the Future" is an essential read for anyone interested in the cutting-edge of AI technology. Whether you are a researcher, practitioner, or simply curious about the future of AI, this book provides a comprehensive and accessible guide to the transformative power of generative AI and LLMs.
Generative Deep Learning
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Author : David Foster
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-06-28
Generative Deep Learning written by David Foster and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-28 with Computers categories.
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
Artificial Intelligence With Python
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Author : Prateek Joshi
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-01-27
Artificial Intelligence With Python written by Prateek Joshi and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with Computers categories.
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.
Artificial Intelligence And Games
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Author : Georgios N. Yannakakis
language : en
Publisher: Springer
Release Date : 2018-02-17
Artificial Intelligence And Games written by Georgios N. Yannakakis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-17 with Computers categories.
This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games. After introductory chapters that explain the background and key techniques in AI and games, the authors explain how to use AI to play games, to generate content for games and to model players. The book will be suitable for undergraduate and graduate courses in games, artificial intelligence, design, human-computer interaction, and computational intelligence, and also for self-study by industrial game developers and practitioners. The authors have developed a website (http://www.gameaibook.org) that complements the material covered in the book with up-to-date exercises, lecture slides and reading.
Generative Ai
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Author : Srinivasa Rao Thumala
language : en
Publisher: SGSH Publications
Release Date : 2025-01-01
Generative Ai written by Srinivasa Rao Thumala and has been published by SGSH Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-01 with Antiques & Collectibles categories.
The book "Generative AI" is a comprehensive exploration of the rapidly evolving field of generative artificial intelligence. It provides readers with a thorough understanding of the foundational concepts, advanced techniques, and diverse applications of generative AI. Key topics covered include foundational technologies like neural networks, autoencoders, and advanced models such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and diffusion models. The book emphasises the transformative potential of generative AI in fields such as healthcare, entertainment, creative arts, and software development. It offers practical insights through hands-on projects, such as building chatbots, creating AI-generated art, and synthesising audio, making it valuable for both beginners and professionals. A distinguishing feature of the book is its focus on ethical considerations, addressing issues like bias, misinformation, and the societal implications of AI-generated content. It also delves into optimisation strategies, scalability, and deployment challenges, providing a well-rounded perspective for readers aiming to implement generative AI in real-world scenarios. With a structured approach, the book balances theoretical concepts and practical applications, supported by detailed case studies and future research directions. The book "Generative AI" benefits readers by providing a thorough understanding of the principles, technologies, and applications of generative artificial intelligence. It balances theoretical insights with practical implementation through hands-on projects like chatbot development, AI-generated art, and audio synthesis. Readers are introduced to diverse applications across industries such as healthcare, entertainment, and software development, enabling them to explore innovative opportunities. The book also addresses critical ethical and societal concerns, fostering responsible AI usage. By discussing future trends, optimisation strategies, and scalability, it equips readers with the knowledge and tools to excel in the rapidly evolving field of generative AI, making it an invaluable resource for students, professionals, and researchers alike.
Generative Ai
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Author : Prabhu TL
language : en
Publisher: NestFame Creations Pvt Ltd.
Release Date : 2025-04-06
Generative Ai written by Prabhu TL and has been published by NestFame Creations Pvt Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-06 with Computers categories.
Generative AI: From Basics to Breakthroughs Unlock the Power of Machines That Imagine, Create, and Build the Future Step into the most transformative era of technology since the invention of the internet. Generative AI is not just reshaping industries—it's redefining what it means to be creative, intelligent, and human. In this groundbreaking guide, you'll explore the fascinating world where algorithms become artists, machines write like humans, and code generates code. Whether you're a developer looking to build the next AI-powered tool, a designer eager to co-create with machines, or simply curious about how tools like ChatGPT, DALL·E, and Stable Diffusion work—this book is your roadmap. 💡 Inside, You’ll Discover: The core building blocks: autoencoders, GANs, transformers, and diffusion models How generative AI powers text, image, audio, video, and code creation Real-world applications across business, education, entertainment, and art The tools, libraries, and platforms that fuel AI development (no coding experience needed!) Case studies from companies like OpenAI, Adobe, GitHub, and Synthesia Crucial conversations on ethics, copyright, bias, and responsible AI use Future trends and how you can ride the wave of the next digital renaissance 📘 Perfect for: Tech professionals & entrepreneurs Designers & digital artists Students, educators & researchers Content creators & marketers Anyone fascinated by the future of intelligence and creativity Whether you're just getting started or seeking to master advanced tools and techniques, Generative AI: From Basics to Breakthroughs is your comprehensive, up-to-date companion to the most exciting technology of our time. Create. Innovate. Elevate. The future isn’t just automated—it’s generated.
Generative Ai
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Author : Maria Johnsen
language : en
Publisher: Maria Johnsen
Release Date : 2024-06-08
Generative Ai written by Maria Johnsen and has been published by Maria Johnsen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-08 with Computers categories.
This book explores the technology behind AI systems that generate new content. We examine how models learn from existing data and use advanced algorithms, aiming to educate readers on the principles, applications, and impact of this transformative field. Featuring case studies from various industries, the book is the result of extensive research. I hope you find it engaging and insightful. It's especially recommended for postgraduate students, as it covers key aspects of generative AI and its future potential.
Generative Ai Foundations In Python
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Author : Carlos Rodriguez
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-07-26
Generative Ai Foundations In Python written by Carlos Rodriguez and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-26 with Computers categories.
Begin your generative AI journey with Python as you explore large language models, understand responsible generative AI practices, and apply your knowledge to real-world applications through guided tutorials Key Features Gain expertise in prompt engineering, LLM fine-tuning, and domain adaptation Use transformers-based LLMs and diffusion models to implement AI applications Discover strategies to optimize model performance, address ethical considerations, and build trust in AI systems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe intricacies and breadth of generative AI (GenAI) and large language models can sometimes eclipse their practical application. It is pivotal to understand the foundational concepts needed to implement generative AI. This guide explains the core concepts behind -of-the-art generative models by combining theory and hands-on application. Generative AI Foundations in Python begins by laying a foundational understanding, presenting the fundamentals of generative LLMs and their historical evolution, while also setting the stage for deeper exploration. You’ll also understand how to apply generative LLMs in real-world applications. The book cuts through the complexity and offers actionable guidance on deploying and fine-tuning pre-trained language models with Python. Later, you’ll delve into topics such as task-specific fine-tuning, domain adaptation, prompt engineering, quantitative evaluation, and responsible AI, focusing on how to effectively and responsibly use generative LLMs. By the end of this book, you’ll be well-versed in applying generative AI capabilities to real-world problems, confidently navigating its enormous potential ethically and responsibly.What you will learn Discover the fundamentals of GenAI and its foundations in NLP Dissect foundational generative architectures including GANs, transformers, and diffusion models Find out how to fine-tune LLMs for specific NLP tasks Understand transfer learning and fine-tuning to facilitate domain adaptation, including fields such as finance Explore prompt engineering, including in-context learning, templatization, and rationalization through chain-of-thought and RAG Implement responsible practices with generative LLMs to minimize bias, toxicity, and other harmful outputs Who this book is for This book is for developers, data scientists, and machine learning engineers embarking on projects driven by generative AI. A general understanding of machine learning and deep learning, as well as some proficiency with Python, is expected.