Download or read book Using Stable Diffusion with Python written by Andrew Zhu (Shudong Zhu) and published by Packt Publishing Ltd. This book was released on 2024-06-03 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master AI image generation by leveraging GenAI tools and techniques such as diffusers, LoRA, textual inversion, ControlNet, and prompt design in this hands-on guide, with key images printed in color Key Features Master the art of generating stunning AI artwork with the help of expert guidance and ready-to-run Python code Get instant access to emerging extensions and open-source models Leverage the power of community-shared models and LoRA to produce high-quality images that captivate audiences Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionStable Diffusion is a game-changing AI tool that enables you to create stunning images with code. The author, a seasoned Microsoft applied data scientist and contributor to the Hugging Face Diffusers library, leverages his 15+ years of experience to help you master Stable Diffusion by understanding the underlying concepts and techniques. You’ll be introduced to Stable Diffusion, grasp the theory behind diffusion models, set up your environment, and generate your first image using diffusers. You'll optimize performance, leverage custom models, and integrate community-shared resources like LoRAs, textual inversion, and ControlNet to enhance your creations. Covering techniques such as face restoration, image upscaling, and image restoration, you’ll focus on unlocking prompt limitations, scheduled prompt parsing, and weighted prompts to create a fully customized and industry-level Stable Diffusion app. This book also looks into real-world applications in medical imaging, remote sensing, and photo enhancement. Finally, you'll gain insights into extracting generation data, ensuring data persistence, and leveraging AI models like BLIP for image description extraction. By the end of this book, you'll be able to use Python to generate and edit images and leverage solutions to build Stable Diffusion apps for your business and users.What you will learn Explore core concepts and applications of Stable Diffusion and set up your environment for success Refine performance, manage VRAM usage, and leverage community-driven resources like LoRAs and textual inversion Harness the power of ControlNet, IP-Adapter, and other methodologies to generate images with unprecedented control and quality Explore developments in Stable Diffusion such as video generation using AnimateDiff Write effective prompts and leverage LLMs to automate the process Discover how to train a Stable Diffusion LoRA from scratch Who this book is for If you're looking to gain control over AI image generation, particularly through the diffusion model, this book is for you. Moreover, data scientists, ML engineers, researchers, and Python application developers seeking to create AI image generation applications based on the Stable Diffusion framework can benefit from the insights provided in the book.

Download or read book Python Deep Learning written by Ivan Vasilev and published by Packt Publishing Ltd. This book was released on 2023-11-24 with total page 362 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master effective navigation of neural networks, including convolutions and transformers, to tackle computer vision and NLP tasks using Python Key Features Understand the theory, mathematical foundations and structure of deep neural networks Become familiar with transformers, large language models, and convolutional networks Learn how to apply them to various computer vision and natural language processing problems Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe field of deep learning has developed rapidly recently and today covers a broad range of applications. This makes it challenging to navigate and hard to understand without solid foundations. This book will guide you from the basics of neural networks to the state-of-the-art large language models in use today. The first part of the book introduces the main machine learning concepts and paradigms. It covers the mathematical foundations, the structure, and the training algorithms of neural networks and dives into the essence of deep learning. The second part of the book introduces convolutional networks for computer vision. We’ll learn how to solve image classification, object detection, instance segmentation, and image generation tasks. The third part focuses on the attention mechanism and transformers – the core network architecture of large language models. We’ll discuss new types of advanced tasks they can solve, such as chatbots and text-to-image generation. By the end of this book, you’ll have a thorough understanding of the inner workings of deep neural networks. You'll have the ability to develop new models and adapt existing ones to solve your tasks. You’ll also have sufficient understanding to continue your research and stay up to date with the latest advancements in the field.What you will learn Establish theoretical foundations of deep neural networks Understand convolutional networks and apply them in computer vision applications Become well versed with natural language processing and recurrent networks Explore the attention mechanism and transformers Apply transformers and large language models for natural language and computer vision Implement coding examples with PyTorch, Keras, and Hugging Face Transformers Use MLOps to develop and deploy neural network models Who this book is for This book is for software developers/engineers, students, data scientists, data analysts, machine learning engineers, statisticians, and anyone interested in deep learning. Prior experience with Python programming is a prerequisite.

Download or read book Learn Python Game Development with ChatGPT written by Micheal Lanham and published by BPB Publications. This book was released on 2024-06-07 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage the power of AI in coding, graphics, design, and intelligence to join the next wave in game development KEY FEATURES ● Teaches the core concepts of game development for 2D, 3D, and AI games. ● Uses AI to assist and guide the reader across several facets of game development. ● Learn to create AI-controlled enemies for your games. DESCRIPTION This book is a comprehensive guide to creating interactive and engaging games, leveraging the capabilities of ChatGPT and other advanced AI technologies. The book starts with prompt engineering and system prompting, building a strong AI foundation for game development. It covers various game genres, from text adventures to 3D shooters, showing AI integration. Each chapter is designed to build on the previous one, ensuring a cohesive learning experience that gradually increases in complexity and depth. Readers will learn game development basics and creative techniques for immersive game worlds. They will use PyZork for text games and Streamlit for enhanced visuals. The book covers AI-generated assets, behavior-driven AI, and advanced topics like isometric world-building and voice-responsive games. Practical projects help readers create their unique games, while GPT agents and AI technologies showcase the future of gaming. By the end of this journey, readers will have a deep understanding of how to create innovative and engaging games using AI, positioning them at the forefront of modern game development. WHAT YOU WILL LEARN ● Master prompt engineering for building games, game assets, and AI-driven games. ● Develop engaging text-based adventures with AI-driven storytelling elements. ● Create 2D games from platformers, isometric worlds, and physics. ● Design AI opponents with behavior-driven logic and adaptive difficulty. ● Introduction to 3D first-person shooters using GPT agents. ● Implement voice recognition and text-to-speech in interactive games. WHO THIS BOOK IS FOR This book is for aspiring or experienced game developers and indie game studios interested in using generative AI to create games faster and explore new possibilities. TABLE OF CONTENTS 1. ChatGPT and the Magic of Prompt Engineering 2. Text Adventure: Entering the Enchanted Realm 3. The AI Chronicles: Text Game Evolution 4. 2D Platformer: Leap into Pixelated Fun! 5. Bot Brawls: AI Opponents Enter the Arena 6. Revving up: Cars, Ramps, and Pymunk 7. Building Isometric Worlds 8. Leveling up with GPT Agents and AutoGen 9. Building a 3D First-Person Shooter 10. Games That Respond to Your Voice 11. The Future Beckons: Developing GPT Games

Download or read book Quick Start Guide to Large Language Models written by Sinan Ozdemir and published by Addison-Wesley Professional. This book was released on 2024-09-26 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Practical, Step-by-Step Guide to Using LLMs at Scale in Projects and Products Large Language Models (LLMs) like Llama 3, Claude 3, and the GPT family are demonstrating breathtaking capabilities, but their size and complexity have deterred many practitioners from applying them. In Quick Start Guide to Large Language Models, Second Edition, pioneering data scientist and AI entrepreneur Sinan Ozdemir clears away those obstacles and provides a guide to working with, integrating, and deploying LLMs to solve practical problems. Ozdemir brings together all you need to get started, even if you have no direct experience with LLMs: step-by-step instructions, best practices, real-world case studies, and hands-on exercises. Along the way, he shares insights into LLMs' inner workings to help you optimize model choice, data formats, prompting, fine-tuning, performance, and much more. The resources on the companion website include sample datasets and up-to-date code for working with open- and closed-source LLMs such as those from OpenAI (GPT-4 and GPT-3.5), Google (BERT, T5, and Gemini), X (Grok), Anthropic (the Claude family), Cohere (the Command family), and Meta (BART and the LLaMA family). Learn key concepts: pre-training, transfer learning, fine-tuning, attention, embeddings, tokenization, and more Use APIs and Python to fine-tune and customize LLMs for your requirements Build a complete neural/semantic information retrieval system and attach to conversational LLMs for building retrieval-augmented generation (RAG) chatbots and AI Agents Master advanced prompt engineering techniques like output structuring, chain-of-thought prompting, and semantic few-shot prompting Customize LLM embeddings to build a complete recommendation engine from scratch with user data that outperforms out-of-the-box embeddings from OpenAI Construct and fine-tune multimodal Transformer architectures from scratch using open-source LLMs and large visual datasets Align LLMs using Reinforcement Learning from Human and AI Feedback (RLHF/RLAIF) to build conversational agents from open models like Llama 3 and FLAN-T5 Deploy prompts and custom fine-tuned LLMs to the cloud with scalability and evaluation pipelines in mind Diagnose and optimize LLMs for speed, memory, and performance with quantization, probing, benchmarking, and evaluation frameworks "A refreshing and inspiring resource. Jam-packed with practical guidance and clear explanations that leave you smarter about this incredible new field." --Pete Huang, author of The Neuron Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.

Download or read book Recent Advancements in Artificial Intelligence written by Richi Nayak and published by Springer Nature. This book was released on with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt:

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

Download or read book Transformers for Natural Language Processing and Computer Vision written by Denis Rothman and published by Packt Publishing Ltd. This book was released on 2024-02-29 with total page 731 pages. Available in PDF, EPUB and Kindle. Book excerpt: The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal Generative AI, risks, and implementations with ChatGPT Plus with GPT-4, Hugging Face, and Vertex AI Key Features Compare and contrast 20+ models (including GPT-4, BERT, and Llama 2) and multiple platforms and libraries to find the right solution for your project Apply RAG with LLMs using customized texts and embeddings Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases Purchase of the print or Kindle book includes a free eBook in PDF format Book DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, applications, and various platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV). The book guides you through different transformer architectures to the latest Foundation Models and Generative AI. You’ll pretrain and fine-tune LLMs and work through different use cases, from summarization to implementing question-answering systems with embedding-based search techniques. You will also learn the risks of LLMs, from hallucinations and memorization to privacy, and how to mitigate such risks using moderation models with rule and knowledge bases. You’ll implement Retrieval Augmented Generation (RAG) with LLMs to improve the accuracy of your models and gain greater control over LLM outputs. Dive into generative vision transformers and multimodal model architectures and build applications, such as image and video-to-text classifiers. Go further by combining different models and platforms and learning about AI agent replication. This book provides you with an understanding of transformer architectures, pretraining, fine-tuning, LLM use cases, and best practices.What you will learn Breakdown and understand the architectures of the Original Transformer, BERT, GPT models, T5, PaLM, ViT, CLIP, and DALL-E Fine-tune BERT, GPT, and PaLM 2 models Learn about different tokenizers and the best practices for preprocessing language data Pretrain a RoBERTa model from scratch Implement retrieval augmented generation and rules bases to mitigate hallucinations Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP Go in-depth into vision transformers with CLIP, DALL-E 2, DALL-E 3, and GPT-4V Who this book is for This book is ideal for NLP and CV engineers, software developers, data scientists, machine learning engineers, and technical leaders looking to advance their LLMs and generative AI skills or explore the latest trends in the field. Knowledge of Python and machine learning concepts is required to fully understand the use cases and code examples. However, with examples using LLM user interfaces, prompt engineering, and no-code model building, this book is great for anyone curious about the AI revolution.

Download or read book Coding Architecture written by Pierpaolo Ruttico and published by Springer Nature. This book was released on 2024-01-30 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a clear picture of how computational processes are gradually permeating and innovating the Architecture, Engineering, and Construction sector, contributing to sustainability and aesthetic evolution. It achieves that by gathering a collection of accounts shared by pioneering professionals involved in this innovation, drawing from recent academic studies, ongoing experimental processes conducted in cutting-edge architectural and engineering offices, as well as innovative industrial applications. The covered subjects span a wide range, including artificial intelligence and robotic manufacturing, the metaverse and 3D printing, strategies to counter CO2 consumption through plug-ins, as well as emerging materials and construction techniques. The chapters feature authors who are pioneers and embrace roles like software developers, architects, process engineers, academics, and forward-thinking entrepreneurs. They represent authoritative references within a broader interconnected cultural and technological system; an eclectic system that finds in computational processes the key to addressing the new challenges of contemporary architecture.

Download or read book Incredible artificial intelligence Easy Diffusion 3 0 The Middle and High School Guide written by Alexander Chesalov and published by Litres. This book was released on 2024-04-11 with total page 387 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is written for middle and high school students.With the help of it and the Easy Diffusion 3.0 artificial intelligence system, you will learn how to create unique and inimitable images that you can use in your studies or for entertainment.The book contains educational information about existing types of artificial intelligence and a wonderful album of more than a hundred illustrations.

Download or read book Digital Signifiers in an Architecture of Information written by Pablo Lorenzo-Eiroa and published by Taylor & Francis. This book was released on 2023-05-31 with total page 491 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book proposes a new critical relationship between computation and architecture, developing a history and theory of representation in architecture to understand and unleash potential means to open up creativity in the field. Historically, architecture has led to spatial representation. Today, computation has established new representational paradigms that can be compared to spatial representations, such as the revolution of perspective in the Renaissance. Architects now use software, robotics, and fabrication tools with very little understanding and participation in how these tools influence, revolutionize, and determine both architecture and its construction today. Why does the discipline of architecture not have a higher degree of authorship in the conception and development of computational technologies that define spatial representation? This book critically explores the relationship between history, theory, and cultural criticism. Lorenzo-Eiroa positions new understandings through parallel historical sections and theories of many revolutionary representational architecture canons displaced by conventional spatial projection. He identifies the architects, artists, mathematicians, and philosophers that were able to revolutionize their disciplines through the development of new technologies, new systems of representation, and new lenses to understand reality. This book frames the discussion by addressing new means to understand and expand architecture authorship in relation to the survey, information, representation, higher dimensional space, Big Data, and Artificial Intelligence – in the pursuit of activating an architecture of information. This will be important reading for upper-level students and researchers of architecture and architectural theory, especially those with a keen interest in computational design and robotic fabrication.

Download or read book The Pioneering Applications of Generative AI written by Kumar, Raghvendra and published by IGI Global. This book was released on 2024-07-17 with total page 360 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrating generative artificial intelligence (AI) into art, design, and media presents a double-edged sword. While it offers unprecedented creative possibilities, it raises ethical concerns, challenges traditional workflows, and requires careful regulation. As AI becomes more prevalent in these fields, there is a pressing need for a comprehensive resource that explores the technology's potential and navigates the complex landscape of its implications. The Pioneering Applications of Generative AI is a pioneering book that addresses these challenges head-on. It provides a deep dive into the evolution, ethical considerations, core technologies, and creative applications of generative AI, offering readers a thorough understanding of this transformative technology. Researchers, academicians, scientists, and research scholars will find this book invaluable in navigating the complexities of generative AI in art, design, and media. With its focus on ethical and responsible AI and discussions on regulatory frameworks, the book equips readers with the knowledge and tools needed to harness the full potential of generative AI while ensuring its responsible and ethical use.

Download or read book Snakes on a spaceship An overview of python in space physics written by Angeline G. Burrell and published by Frontiers Media SA. This book was released on 2023-07-20 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Generative AI in Action written by Amit Bahree and published by Simon and Schuster. This book was released on 2024-10-29 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI can transform your business by streamlining the process of creating text, images, and code. This book will show you how to get in on the action! Generative AI in Action is the comprehensive and concrete guide to generative AI you’ve been searching for. It introduces both AI’s fundamental principles and its practical applications in an enterprise context—from generating text and images for product catalogs and marketing campaigns, to technical reporting, and even writing software. Inside, author Amit Bahree shares his experience leading Generative AI projects at Microsoft for nearly a decade, starting well before the current GPT revolution. Inside Generative AI in Action you will find: • A practical overview of of generative AI applications • Architectural patterns, integration guidance, and best practices for generative AI • The latest techniques like RAG, prompt engineering, and multi-modality • The challenges and risks of generative AI like hallucinations and jailbreaks • How to integrate generative AI into your business and IT strategy Generative AI in Action is full of real-world use cases for generative AI, showing you where and how to start integrating this powerful technology into your products and workflows. You’ll benefit from tried-and-tested implementation advice, as well as application architectures to deploy GenAI in production at enterprise scale. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology In controlled environments, deep learning systems routinely surpass humans in reading comprehension, image recognition, and language understanding. Large Language Models (LLMs) can deliver similar results in text and image generation and predictive reasoning. Outside the lab, though, generative AI can both impress and fail spectacularly. So how do you get the results you want? Keep reading! About the book Generative AI in Action presents concrete examples, insights, and techniques for using LLMs and other modern AI technologies successfully and safely. In it, you’ll find practical approaches for incorporating AI into marketing, software development, business report generation, data storytelling, and other typically-human tasks. You’ll explore the emerging patterns for GenAI apps, master best practices for prompt engineering, and learn how to address hallucination, high operating costs, the rapid pace of change and other common problems. What's inside • Best practices for deploying Generative AI apps • Production-quality RAG • Adapting GenAI models to your specific domain About the reader For enterprise architects, developers, and data scientists interested in upgrading their architectures with generative AI. About the author Amit Bahree is Principal Group Product Manager for the Azure AI engineering team at Microsoft. The technical editor on this book was Wee Hyong Tok. Table of Contents Part 1 1 Introduction to generative AI 2 Introduction to large language models 3 Working through an API: Generating text 4 From pixels to pictures: Generating images 5 What else can AI generate? Part 2 6 Guide to prompt engineering 7 Retrieval-augmented generation: The secret weapon 8 Chatting with your data 9 Tailoring models with model adaptation and fine-tuning Part 3 10 Application architecture for generative AI apps 11 Scaling up: Best practices for production deployment 12 Evaluations and benchmarks 13 Guide to ethical GenAI: Principles, practices, and pitfalls A The book’s GitHub repository B Responsible AI tools

Download or read book Generative AI for Entrepreneurs in a Hurry written by Mohak Agarwal and published by Notion Press. This book was released on 2023-02-27 with total page 200 pages. Available in PDF, EPUB and Kindle. Book excerpt: Generative AI for Entrepreneurs in a Hurry is a comprehensive guide to understanding and leveraging AI to achieve success in the business world. Written by entrepreneur and AI expert, Mohak Agarwal, this book takes the reader on a journey of understanding how AI can be used to create powerful, high-impact strategies for success. With the rise of large language models like gpt-3, midjourney and chatGPT, Agarwal provides a comprehensive guide to leveraging these tools to create new business models and strategies. The book provides step-by-step guidance on how to leverage AI to create new opportunities in marketing, customer service, product development, and more. Generative AI for Entrereners in a Hurry is the perfect guide for entrepreneurs looking to take advantage of the power of AI. The book houses a list of more than 150 start-ups in the Generative AI space with details about the start-up like what they do founders and funding details

Download or read book A Beginner s Guide to Medical Application Development with Deep Convolutional Neural Networks written by Snehan Biswas and published by CRC Press. This book was released on 2024-12-02 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book serves as a source of introductory material and reference for medical application development and related technologies by providing the detailed implementation of cutting-edge deep learning methodologies. It targets cloud-based advanced medical application developments using open-source Python-based deep learning libraries. It includes code snippets and sophisticated convolutional neural networks to tackle real-world problems in medical image analysis and beyond. Features: Provides programming guidance for creation of sophisticated and reliable neural networks for image processing. Incorporates the comparative study on GAN, stable diffusion, and its application on medical image data augmentation. Focuses on solving real-world medical imaging problems. Discusses advanced concepts of deep learning along with the latest technology such as GPT, stable diffusion, and ViT. Develops applicable knowledge of deep learning using Python programming, followed by code snippets and OOP concepts. This book is aimed at graduate students and researchers in medical data analytics, medical image analysis, signal processing, and deep learning.

Download or read book Implementing MLOps in the Enterprise written by Yaron Haviv and published by "O'Reilly Media, Inc.". This book was released on 2023-11-30 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production. Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. By automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs. You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book will help you: Learn the MLOps process, including its technological and business value Build and structure effective MLOps pipelines Efficiently scale MLOps across your organization Explore common MLOps use cases Build MLOps pipelines for hybrid deployments, real-time predictions, and composite AI Learn how to prepare for and adapt to the future of MLOps Effectively use pre-trained models like HuggingFace and OpenAI to complement your MLOps strategy

Download or read book AI Assisted Programming written by Tom Taulli and published by "O'Reilly Media, Inc.". This book was released on 2024-04-10 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get practical advice on how to leverage AI development tools for all stages of code creation, including requirements, planning, design, coding, debugging, testing, and documentation. With this book, beginners and experienced developers alike will learn how to use a wide range of tools, from general-purpose LLMs (ChatGPT, Gemini, and Claude) to code-specific systems (GitHub Copilot, Tabnine, Cursor, and Amazon CodeWhisperer). You'll also learn about more specialized generative AI tools for tasks such as text-to-image creation. Author Tom Taulli provides a methodology for modular programming that aligns effectively with the way prompts create AI-generated code. This guide also describes the best ways of using general purpose LLMs to learn a programming language, explain code, or convert code from one language to another. This book examines: The core capabilities of AI-based development tools Pros, cons, and use cases of popular systems such as GitHub Copilot and Amazon CodeWhisperer Ways to use ChatGPT, Gemini, Claude, and other generic LLMs for coding Using AI development tools for the software development lifecycle, including requirements, planning, coding, debugging, and testing Prompt engineering for development Using AI-assisted programming for tedious tasks like creating regular expressions, starter code, object-oriented programming classes, and GitHub Actions How to use AI-based low-code and no-code tools, such as to create professional UIs