Wydawca: Packt Publishing
Natalie Denmeade
This book describes how teachers can use Gamification design within the Moodle Learning Management System. Game elements can be included in course design by using, badges, rubrics, custom grading scales, forums, and conditional activities. Moodle courses do not have to be solo-learning experiences that replicate Distance Education models. The Gamification design process starts by profiling players and creating levels of achievement towards meeting learning outcomes. Each task is defined, valued, and sequenced. Motivation loops are devised to keep the momentum going. In a gaming studio, this approach would require a team of specialists with a large budget and time frames. Preparing for a class rarely has these optimal conditions. The approach used in this book is to introduce game elements into the course design gradually. First, apply gamification to just one lesson and then build up to gamifying a series of lessons over a term. Each example will indicate the difficulty level and time investment. Try it out to see what is most effective with your learners and choose wisely in your use of technology. By the end of this book, you will be able to create Moodle courses that incorporate choice, communication,challenge, and creativity.
Lauren S. Ferro
Are you looking at implementing gamification techniques for your business and wondering where to get a complete rundown of all the tricks and techniques? Well, you have come to the right place!This book will start right from the basics such as gameplay elements and their functionalities before gradually moving onto creating your first gamification project from scratch. You’ll be given the tools and shown how to perform various techniques for creating gamified applications in different contexts. Finally, you will implement various game elements into Unity, publish your own task management application, and get to know the best practices and approaches when designing gamified experiences.
Holly Picano
Unveil the extraordinary capabilities of the groundbreaking AI model, DALL-E 3, as it transforms text prompts into accurate images. This book addresses the challenge of creating meaningful images by writing prompts, guiding you step by step through creating stunning visual art regardless of your skill level.Prepare to delve deep into the inner workings of DALL-E 3's architecture and training process. With clear explanations, practical tutorials, and real-world examples that can be easily applied, you’ll unlock secrets to creating awe-inspiring AI-generated art, from fine art prints to digital designs. This book provides comprehensive insights into various lens options, camera angles, lighting techniques, and art movements, helping you integrate AI capabilities with your artistic skills. You’ll also learn to create NFTs that can be monetized and gain invaluable insights into designing compelling covers, all within the ethical boundaries of AI-generated art. And with the invaluable prompt cheat sheet by your side, you’ll hone your skills in formulating captivating prompts for diverse purposes.By the end of this book, you’ll have learned how to produce generative AI art at a rapid pace and relatively low cost and push the boundaries of imagination with DALL-E 3.
Josh Kalin
Developing Generative Adversarial Networks (GANs) is a complex task, and it is often hard to find code that is easy to understand.This book leads you through eight different examples of modern GAN implementations, including CycleGAN, simGAN, DCGAN, and 2D image to 3D model generation. Each chapter contains useful recipes to build on a common architecture in Python, TensorFlow and Keras to explore increasingly difficult GAN architectures in an easy-to-read format. The book starts by covering the different types of GAN architecture to help you understand how the model works. This book also contains intuitive recipes to help you work with use cases involving DCGAN, Pix2Pix, and so on. To understand these complex applications, you will take different real-world data sets and put them to use.By the end of this book, you will be equipped to deal with the challenges and issues that you may face while working with GAN models, thanks to easy-to-follow code solutions that you can implement right away.
Kailash Ahirwar
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.
Juan Pablo Bustos, Luis Lopez Soria, Dr....
Explore the transformative potential of GenAI in the application development lifecycle. Through concrete examples, you will go through the process of ideation and integration, understanding the tradeoffs and the decision points when integrating GenAI.With recent advances in models like Google Gemini, Anthropic Claude, DALL-E and GPT-4o, this timely resource will help you harness these technologies through proven design patterns.We then delve into the practical applications of GenAI, identifying common use cases and applying design patterns to address real-world challenges. From summarization and metadata extraction to intent classification and question answering, each chapter offers practical examples and blueprints for leveraging GenAI across diverse domains and tasks. You will learn how to fine-tune models for specific applications, progressing from basic prompting to sophisticated strategies such as retrieval augmented generation (RAG) and chain of thought.Additionally, we provide end-to-end guidance on operationalizing models, including data prep, training, deployment, and monitoring. We also focus on responsible and ethical development techniques for transparency, auditing, and governance as crucial design patterns.
Generative AI Art. Unleash Your Creativity with Generative AI Art for Beginners
Oliver Theobald
The course introduces the basic concepts of artificial intelligence and its application in art, making it accessible even to those without a technical background. This foundation paves the way for exploring the nuances of effective prompt crafting, a critical skill for generating bespoke AI artwork.The course focuses on hands-on demonstrations with leading AI art software, including Craiyon and Midjourney, offering step-by-step guides to harness these tools effectively. Through practical examples, learners will understand how to navigate image prompts, masking techniques, framing, and lighting to enhance the visual appeal of their creations. The significance of navigating these elements is underscored, highlighting their role in achieving consistency and originality in AI-generated art.The course wraps up by delving into the remixing of popular art styles, the art of creating compelling text prompts, and the critical aspects of image rights, ethics, privacy, and originality in the digital art space. By concluding with recommended resources, learners are equipped to continue their journey in AI art, fueled by inspiration and a solid understanding of the field's possibilities and responsibilities.
Generative AI at AWS. Turn business strategy into production-ready AI applications and agents
Nestor Gandara, Eduardo Ordax, Srikanth Daggumalli, Ashutosh...
Cut through the noise around generative AI and learn how to turn promising ideas into secure, scalable solutions on AWS. This book helps you connect business priorities with technical execution, so you can identify worthwhile use cases, select the right models and services, and move from pilot to production with confidence.You explore the fundamentals of generative AI, understand how foundation models and agents work, and see where services such as Amazon Bedrock AgentCore and Amazon SageMaker AI fit into a modern AI stack. From there, the book guides you through preparing data, building an MVP, deploying production-ready applications, and designing for scalability, governance, and responsible AI.Real-world industry examples and practical decision frameworks help you evaluate when to use generative AI, when traditional approaches are a better fit, and how to measure business value. You also examine advanced topics such as agentic AI, emerging patterns, and the future direction of enterprise AI.By the end of this book, you will be able to plan, build, and govern generative AI solutions on AWS that deliver measurable value for your organization.