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Author: Anand Vemula
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
Generative AI Projects: A Hands-On Guide is an immersive and practical resource designed to take readers on a journey through the fascinating world of generative artificial intelligence. This comprehensive guide covers the fundamental concepts and advanced techniques necessary for building and deploying generative AI models across various domains. Starting with an introduction to generative AI, the book explains the core principles, history, and evolution of this cutting-edge technology. It delves into key concepts such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Large Language Models (LLMs), providing readers with a solid foundation to understand how these models generate new data. The book is structured around a series of hands-on projects that progressively build in complexity. Each project is designed to be both educational and practical, offering step-by-step instructions and code examples. Project 1: Text Generation with LLMs focuses on building and fine-tuning language models for generating coherent and contextually relevant text. Readers will learn about data collection, model training, and deployment techniques. Project 2: Image Generation with GANs guides readers through the process of creating high-quality images using GANs. It covers the fundamentals of GANs, training procedures, and methods to evaluate and enhance image quality. Project 3: Music Generation with VAEs explores how to generate musical compositions. This project includes data representation for music, building VAEs, and integrating generated music into applications. Project 4: Video Generation and Synthesis tackles the complexities of video generation, including data preprocessing, model training, and evaluation of generated videos for use in entertainment and media. Advanced projects delve deeper into specific applications, such as generative art, chatbots, and healthcare. Each section emphasizes real-world applications, ethical considerations, and best practices for deploying and monitoring generative AI models. This guide is ideal for AI enthusiasts, data scientists, and developers looking to expand their knowledge and skills in generative AI. With a focus on practical implementation and real-world applications, it equips readers with the tools and knowledge to innovate and excel in the field of generative AI.
Author: Anand Vemula
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0
Get Book Here
Book Description
Generative AI Projects: A Hands-On Guide is an immersive and practical resource designed to take readers on a journey through the fascinating world of generative artificial intelligence. This comprehensive guide covers the fundamental concepts and advanced techniques necessary for building and deploying generative AI models across various domains. Starting with an introduction to generative AI, the book explains the core principles, history, and evolution of this cutting-edge technology. It delves into key concepts such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Large Language Models (LLMs), providing readers with a solid foundation to understand how these models generate new data. The book is structured around a series of hands-on projects that progressively build in complexity. Each project is designed to be both educational and practical, offering step-by-step instructions and code examples. Project 1: Text Generation with LLMs focuses on building and fine-tuning language models for generating coherent and contextually relevant text. Readers will learn about data collection, model training, and deployment techniques. Project 2: Image Generation with GANs guides readers through the process of creating high-quality images using GANs. It covers the fundamentals of GANs, training procedures, and methods to evaluate and enhance image quality. Project 3: Music Generation with VAEs explores how to generate musical compositions. This project includes data representation for music, building VAEs, and integrating generated music into applications. Project 4: Video Generation and Synthesis tackles the complexities of video generation, including data preprocessing, model training, and evaluation of generated videos for use in entertainment and media. Advanced projects delve deeper into specific applications, such as generative art, chatbots, and healthcare. Each section emphasizes real-world applications, ethical considerations, and best practices for deploying and monitoring generative AI models. This guide is ideal for AI enthusiasts, data scientists, and developers looking to expand their knowledge and skills in generative AI. With a focus on practical implementation and real-world applications, it equips readers with the tools and knowledge to innovate and excel in the field of generative AI.
Author: Kailash Ahirwar
Publisher: Packt Publishing Ltd
ISBN: 1789134196
Category : Mathematics
Languages : en
Pages : 310
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Book Description
Explore various Generative Adversarial Network architectures using the Python ecosystem Key FeaturesUse different datasets to build advanced projects in the Generative Adversarial Network domainImplement projects ranging from generating 3D shapes to a face aging applicationExplore the power of GANs to contribute in open source research and projectsBook Description Generative Adversarial Networks (GANs) have the potential to build next-generation models, as they can mimic any distribution of data. Major research and development work is being undertaken in this field since it is one of the rapidly growing areas of machine learning. This book will test unsupervised techniques for training neural networks as you build seven end-to-end projects in the GAN domain. Generative Adversarial Network Projects begins by covering the concepts, tools, and libraries that you will use to build efficient projects. You will also use a variety of datasets for the different projects covered in the book. The level of complexity of the operations required increases with every chapter, helping you get to grips with using GANs. You will cover popular approaches such as 3D-GAN, DCGAN, StackGAN, and CycleGAN, and you’ll gain an understanding of the architecture and functioning of generative models through their practical implementation. By the end of this book, you will be ready to build, train, and optimize your own end-to-end GAN models at work or in your own projects. What you will learnTrain a network on the 3D ShapeNet dataset to generate realistic shapesGenerate anime characters using the Keras implementation of DCGANImplement an SRGAN network to generate high-resolution imagesTrain Age-cGAN on Wiki-Cropped images to improve face verificationUse Conditional GANs for image-to-image translationUnderstand the generator and discriminator implementations of StackGAN in KerasWho this book is for If you’re a data scientist, machine learning developer, deep learning practitioner, or AI enthusiast looking for a project guide to test your knowledge and expertise in building real-world GANs models, this book is for you.
Author: Anand Vemula
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
Generative AI in the Classroom: A Practical Guide for Educators offers a comprehensive exploration of how generative artificial intelligence (AI) can revolutionize teaching and learning in modern education. This practical guide is tailored for educators seeking to enhance their classrooms with cutting-edge AI technologies, providing actionable insights, detailed case studies, and hands-on tutorials. The book is divided into four main parts, each focusing on a critical aspect of integrating generative AI into educational settings: Part I: Introduction to Generative AI This section introduces the fundamental concepts of AI and machine learning, tracing their historical development and current applications across various fields. It explains what generative AI is, detailing different types such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Transformers. The section also discusses the transformative potential of generative AI in education, highlighting both its benefits and ethical challenges. Part II: Implementing Generative AI in the Classroom Here, the book provides a step-by-step guide on integrating AI into the curriculum. It helps educators identify suitable subjects and design AI-infused lesson plans, supported by case studies of successful implementations. The section covers AI-powered teaching tools, such as automated grading systems and personalized feedback mechanisms, offering criteria for evaluating and selecting the right tools for different educational contexts. Part III: Practical Applications and Case Studies This part showcases real-world applications of generative AI in education through detailed case studies and success stories. It includes practical examples and project ideas for students, resources for managing AI projects, and guidelines for fostering collaborative learning with AI. Readers will find hands-on tutorials and complete solutions, demonstrating how to create AI projects, enhance group work, and utilize AI for virtual classrooms and remote learning. Part IV: Future of Generative AI in Education The final section looks ahead to emerging trends and technologies in AI, predicting their future impact on education. It discusses innovations like augmented reality, emotion AI, and blockchain, offering strategies for preparing educators and students for these advancements. The book also addresses critical policy and ethical considerations, such as data privacy, equitable access, and developing responsible AI use policies. Generative AI in the Classroom: A Practical Guide for Educators concludes with strategic recommendations for educators and policymakers, summarizing key insights and emphasizing the transformative potential of generative AI to create more personalized, engaging, and effective educational experiences. This guide is an invaluable resource for educators ready to embrace the future of learning with generative AI.
Author: Dr Bienvenue Maula
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
"Generative AI: The Beginner's Guide" is a comprehensive introduction to the world of generative artificial intelligence. Written for readers who are new to the subject, this book explains the basics of how generative AI works, what it can do, and how it is used in various industries. Starting with the fundamentals of machine learning, the book gradually introduces readers to the key concepts and techniques used in generative AI. Readers will learn about the different types of generative models, such as GANs and VAEs, and how they can be trained to generate images, music, text, and more. The book also covers important topics such as data preprocessing, model evaluation, and ethical considerations in AI. Throughout the book, readers will find clear explanations, helpful examples, and practical tips for implementing generative AI projects. Whether you are a student, a programmer, or a hobbyist, "Generative AI for Beginners" provides an accessible and engaging introduction to this exciting field. With this book as your guide, you will be able to create your own generative AI models and explore the possibilities of this rapidly evolving technology.
Author: Anand Vemula
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
Generative AI with Python and TensorFlow: A Complete Guide to Mastering AI Models is a comprehensive resource for anyone looking to delve into the world of generative artificial intelligence. Introduction Overview of Generative AI: Understand the basic concepts, history, and significance of generative AI. Importance of Generative AI: Learn about the transformative potential of generative AI in various industries. Applications and Use Cases: Explore real-world applications of generative AI in fields such as art, music, text generation, and data augmentation. Overview of Python and TensorFlow: Get an introduction to the essential tools and libraries used for building generative AI models. Getting Started: Set up your development environment, install necessary libraries, and take your first steps with TensorFlow. Fundamentals of Machine Learning Supervised vs. Unsupervised Learning: Understand the differences and use cases of these two primary types of machine learning. Neural Networks Basics: Learn the fundamental concepts of neural networks and their role in AI. Introduction to Deep Learning: Dive deeper into the advanced techniques of deep learning and its applications in generative AI. Key Concepts in Generative AI: Familiarize yourself with the essential concepts and terminologies in generative AI. Generative Models Understanding Generative Models: Explore the theoretical foundations of generative models. Types of Generative Models: Learn about various types of generative models, including VAEs, GANs, autoregressive models, and flow-based models. Variational Autoencoders (VAEs): Delve into the theory behind VAEs, build and train VAEs with TensorFlow, and explore their use cases. Generative Adversarial Networks (GANs): Get introduced to GANs, understand their architecture, implement GANs with TensorFlow, and learn advanced GAN techniques. Autoregressive Models: Understand autoregressive models, implement them with TensorFlow, and explore their applications. Flow-based Models: Learn about flow-based models, build them with TensorFlow, and explore their practical applications. Advanced Topics Transfer Learning for Generative Models: Explore how transfer learning can be applied to generative models. Conditional Generative Models: Understand and implement models that generate outputs conditioned on specific inputs. Multimodal Generative Models: Learn about models that can generate multiple types of data simultaneously. Reinforcement Learning in Generative AI: Explore the intersection of reinforcement learning and generative AI. Practical Applications Image Generation and Style Transfer: Create stunning images and apply style transfer techniques. Text Generation and Natural Language Processing: Generate coherent and contextually relevant text using advanced NLP techniques. Music and Sound Generation: Compose music and generate new sounds using generative AI. Data Augmentation for Machine Learning: Improve your machine learning models by augmenting your datasets with generative models. Hands-On Projects Project 1: Creating Art with GANs: Step-by-step guide to building a GAN to generate art. Project 2: Text Generation with LSTM: Implement an LSTM model for generating text. Project 3: Building a VAE for Image Reconstruction: Learn how to build and train a VAE for image reconstruction. Project 4: Music Generation with RNNs: Create a music generation model using RNNs.
Author: Vijay Kanabar
Publisher: Sams Publishing
ISBN: 0138297320
Category : Business & Economics
Languages : en
Pages : 420
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Book Description
In a world where technology is rapidly evolving, the fusion of project management and artificial intelligence stands at the forefront of innovation. The AI Revolution in Project Management delves deep into the transformative power of generative AI tools that promise to reshape industries, and revolutionize how we manage projects. Whether you're looking to build dynamic teams using AI, choose a project development approach, or monitor project performance, this book has got you covered. Each chapter provides insightful narratives and includes a supplemental Technical Guide that provides tips on using the AI technology. With case studies and prompts, the dialogues showcase AI in action, from stakeholder engagement to risk management. Dive in with experts who’ve spent countless hours using these AI tools in project scenarios to offer a transparent view into generative AI-driven project management. In this book you'll learn: How to create prompts that generate meaningful and actionable insights tailored for your projects When to use AI to enhance decision-making, super-charge productivity, and elevate overall project efficiency Which generative AI models and plug-ins to use for specific project scenarios, ensuring seamless integration and maximum efficiency "AI is not just a buzzword; it’s a tool reshaping how we manage projects and engage with stakeholders." - From the Foreward by Ricardo Viana Vargas, Ph.D. Ricardo is an experienced leader in global operations, project management, business transformation, and crisis management. As founder and managing director of Macrosolutions, a consulting firm with international operations in energy, infrastructure, IT, oil, and finance, he managed more than $20 billion in international projects in the past 25 years. Update As AI products continue to evolve, information published in this book may change. Please note that as of February 2024, there is a name change for Bing Chat and Bard Chat. Microsoft Bing Chat is now Copilot: https://copilot.microsoft.com/. Google Bard is now Gemini: https://gemini.google.com/.
Author: I. Almeida
Publisher: Now Next Later AI
ISBN: 0645977993
Category : Business & Economics
Languages : en
Pages : 529
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Book Description
2024 Edition. Free access to the AI Academy! One of the books in this collection is shortlisted for the 2023 HARVEY CHUTE Book Awards recognizing emerging talent and outstanding works in the genre of Business and Enterprise Non-Fiction. Byte-sized Learning AI series by Now Next Later AI: Practical guides providing senior decision-makers with a clear, accessible roadmap for harnessing the power of generative AI, enhancing innovation, and boosting business outcomes. Save by buying the entire 3 book series in one single collection and gain free access to the AI Academy platform. There you can view free course modules, test your knowledge through quizzes, attend webinars, and engage in discussion with other readers. Book: Generative AI Transformation Blueprint This practical and concise guide provides senior decision-makers with a clear, accessible roadmap for harnessing the power of generative AI, enhancing innovation, and boosting business outcomes. Drawing on insights from AI-enabled business transformations in diverse sectors, it presents a validated strategic approach. This blueprint not only outlines best practices but also showcases pioneering use cases, integrating them into a cohesive framework for practical implementation. This scenario-based approach helps leaders understand where and how to apply the practices outlined. Spanning across areas from strategic alignment and talent development to ethical governance and sustaining a competitive edge amid relentless underlying progress, it delivers clarity for charting an optimal Generative AI roadmap. Book: Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype Shortlisted for the 2023 HARVEY CHUTE Explore the transformative potential of technologies like GPT-4 and Claude 2. These large language models (LLMs) promise to reshape how businesses operate. Aimed at non-technical business leaders, this guide offers a pragmatic approach to leveraging LLMs for tangible benefits, while ensuring ethical considerations aren't sidelined. LLMs can refine processes in marketing, software development, HR, R&D, customer service, and even legal operations. But it's essential to approach them with a balanced view. In this guide, you'll: - Learn about the rapid advancements of LLMs. - Understand complex concepts in simple terms. - Discover practical business applications. - Get strategies for smooth integration. - Assess potential impacts on your team. - Delve into the ethics of deploying LLMs. With a clear aim to inform rather than influence, this book is your roadmap to adopting LLMs thoughtfully, maximizing benefits, and minimizing risks. Let's move beyond the noise and understand how LLMs can genuinely benefit your business. Book: Artificial Intelligence Fundamentals for Business Leaders: Up to Date With Generative AI The perfect guide to help non-technical business leaders understand the power of AI: Machine Learning, Neural Networks, and Data Management. Up to date with Generative AI. More Than a Book Collection By purchasing this series, you will also be granted free access to the AI Academy platform. There you can test your knowledge through end-of-chapter quizzes and engage in discussion with other readers. You will also receive free modules and 50% discount toward the enrollment in the self-paced course of the same name and enjoy video summary lessons, instructor-graded assignments, and live sessions. A course certificate will be awarded upon successful completion. AI Academy by Now Next Later AI We are the most trusted and effective learning platform dedicated to empowering leaders with the knowledge and skills needed to harness the power of AI safely and ethically. We are a human-centric organization. Chat with us anytime.
Author: Anand Vemula
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
"Generative AI Business Applications: Transforming Industries and Innovation" explores the dynamic intersection of generative AI technology and its impactful applications across various industries. Through a comprehensive examination, the book navigates readers through the evolution of generative AI, from its conceptual roots to its current state of transformative potential. The book begins by demystifying generative AI, offering a clear understanding of its key concepts, terminologies, and historical background. Readers delve into the workings of neural networks, deep learning, and different types of generative models such as GANs, VAEs, and Transformers. Current trends, major players, and future directions in the generative AI landscape are meticulously examined, providing a holistic view of the rapidly evolving field. Part II of the book delves into the practical applications of generative AI in business contexts. From personalized content creation and marketing strategies to fraud detection in finance and drug discovery in healthcare, each chapter presents real-world examples, case studies, and code tutorials to illustrate the power and versatility of generative AI across diverse sectors. Part III guides readers through the strategic planning and technical implementation of generative AI projects. It addresses challenges, opportunities, and ethical considerations, providing actionable insights for successful integration into existing systems. In the final section, the book explores future trends and innovations in generative AI, offering predictions, scenarios, and strategies for staying ahead in a rapidly evolving landscape. It emphasizes continuous learning, adaptation, and readiness to embrace emerging technologies. "Generative AI Business Applications" serves as a comprehensive guide for business leaders, data scientists, and technologists seeking to leverage generative AI for transformative impact in their respective industries.
Author: Anand Vemula
Publisher: Anand Vemula
ISBN:
Category : Computers
Languages : en
Pages : 123
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Book Description
This book covers the fundamentals of generative AI, providing an in-depth understanding of key concepts, algorithms, and techniques that power AI-driven content creation. Starting with an introduction to the basics of generative AI, the book explains the theoretical foundations and evolution of generative models, highlighting the significance of this technology in various domains such as image synthesis, text generation, and more. Readers will explore the different types of machine learning, including supervised, unsupervised, and reinforcement learning, and understand their role in the development of generative models. The guide dives into essential Python libraries like TensorFlow, PyTorch, NumPy, and Pandas, offering a hands-on approach to building generative models from scratch. Each chapter is packed with practical examples, case studies, and real-world scenarios that demonstrate the application of these models in various fields, including art, music, and conversational AI. Key topics include Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), flow-based models, autoregressive models, and transformer-based models like GPT. The book also addresses the ethical considerations surrounding generative AI, providing insights into the challenges of bias, fairness, and misinformation. Readers will benefit from step-by-step tutorials that guide them through the process of implementing and optimizing generative models, complete with code examples and hands-on exercises. Additionally, the book offers advanced techniques for improving model performance and stability, ensuring that readers are well-prepared to tackle complex AI projects. Whether you're a beginner looking to understand the basics of generative AI or an experienced developer aiming to enhance your skills, "Mastering Generative AI with Python: A Hands-On Guide" serves as an essential resource for anyone interested in the rapidly evolving field of generative AI.
Author: Paul Boudreau
Publisher:
ISBN: 9781687550941
Category :
Languages : en
Pages : 184
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Book Description
Author Paul Boudreau shares the keys to project management success using a modern approach: artificial intelligence. Within the pages of Applying Artificial Intelligence to Project Management, Boudreau describes five AI tools in concept and how they apply directly to project success, as well as the strategy and method to use to purchase and implement AI tools for project management. Understand the difference between automating a task and changing it by using AI. Discover how AI uses data and the importance of data maintenance. Learn why projects fail and how using artificial intelligence for project management improves project success rates. Read project management success stories in one of the best business books on machine learning, and prepare to leave behind that 50 percent project success rate for one that's 95 percent or higher.
