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Artificial Intelligence with Python

Artificial Intelligence with Python
Author: Prateek Joshi
Publisher: Packt Publishing Ltd
Total Pages: 437
Release: 2017-01-27
Genre: Computers
ISBN: 1786469677
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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 Deep Learning

Generative Deep Learning
Author: David Foster
Publisher: "O'Reilly Media, Inc."
Total Pages: 360
Release: 2019-06-28
Genre: Computers
ISBN: 1492041890
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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

Introduction to Generative AI

Introduction to Generative AI
Author: Numa Dhamani
Publisher: Simon and Schuster
Total Pages: 334
Release: 2024-02-27
Genre: Computers
ISBN: 1633437191
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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

Introducing MLOps

Introducing MLOps
Author: Mark Treveil
Publisher: "O'Reilly Media, Inc."
Total Pages: 171
Release: 2020-11-30
Genre: Computers
ISBN: 1098116429
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More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized

Deep Learning for Coders with fastai and PyTorch

Deep Learning for Coders with fastai and PyTorch
Author: Jeremy Howard
Publisher: O'Reilly Media
Total Pages: 624
Release: 2020-06-29
Genre: Computers
ISBN: 1492045497
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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

Introduction to Artificial Intelligence and Generative AI for Novice

Introduction to Artificial Intelligence and Generative AI for Novice
Author: Adam Neural
Publisher:
Total Pages: 0
Release: 2023-06-25
Genre:
ISBN: 9781088183748
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Artificial intelligence (AI) is currently one of the most talked-about and significant modern technologies. It is being utilized more frequently across a wide range of businesses to enhance workflows, offer individualized experiences, and even assist in resolving difficult societal problems. Although AI is becoming more commonplace, many people are still confused about what it is and how it functions. "This book" is useful in this situation. This manual aims to give a thorough yet understandable introduction to AI. It discusses the development of AI, its various subfields, and its applications in sectors like healthcare, finance, and retail. It also covers the ethical and societal ramifications of AI, such as issues with bias, privacy, and the effect on employment. The approachability of "This book" is one of its main advantages. The manual's straightforward, concise writing makes it simple for readers to comprehend the ideas without becoming lost in technical jargon. In order to assist readers, apply what they have learned to their own commercial or personal initiatives, it contains real-world examples and useful exercises. "This book" is the ideal tool for learning more about AI, whether you are a business owner trying to integrate AI into your operations or are just curious about the subject. By the book's conclusion, readers will be well-versed in the foundations of AI and able to use this technology to accomplish their objectives. It is more crucial than ever to acquire a fundamental understanding of this potent technology in a world where AI is progressively influencing how we conduct our daily lives. With "This book," readers will be well-prepared to traverse the complicated world of artificial intelligence and use it to streamline their lives and accomplish their goals. So, let's get started and together explore the transformational possibilities of AI.

Applications of Generative AI

Applications of Generative AI
Author: Zhihan Lyu
Publisher: Springer Nature
Total Pages: 607
Release:
Genre:
ISBN: 3031462386
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Generative AI with Tensor Flow

Generative AI with Tensor Flow
Author: Anand Vemula
Publisher: Anand Vemula
Total Pages: 71
Release:
Genre: Computers
ISBN:
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"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.

Introduction to Artificial Intelligence and Generative AI for Novice

Introduction to Artificial Intelligence and Generative AI for Novice
Author: Adam Neural
Publisher:
Total Pages: 0
Release: 2023-06-24
Genre:
ISBN: 9781312406124
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Artificial intelligence (AI) is currently one of the most talked-about and significant modern technologies. It is being utilized more frequently across a wide range of businesses to enhance workflows, offers individualized experiences, and even assist in resolving difficult societal problems. Although AI is becoming more commonplace, many people are still confused about what it is and how it functions. "This book" is useful in this situation. This manual aims to give a thorough yet understandable introduction to AI. It discusses the development of AI, its various subfields, and its applications in sectors like healthcare, finance, and retail. It also covers the ethical and societal ramifications of AI, such as issues with bias, privacy, and the effect on employment. The approachability of "This book" is one of its main advantages. The manual's straightforward, concise writing makes it simple for readers to comprehend the ideas without becoming lost in technical jargon. In order to assist readers, apply what they have learned to their own commercial or personal initiatives, it contains real-world examples and useful exercises. "This book" is the ideal tool for learning more about AI, whether you are a business owner trying to integrate AI into your operations or are just curious about the subject. By the book's conclusion, readers will be well-versed in the foundations of AI and able to use this technology to accomplish their objectives. It is more crucial than ever to acquire a fundamental understanding of this potent technology in a world where AI is progressively influencing how we conduct our daily lives. With "This book," readers will be well-prepared to traverse the complicated world of artificial intelligence and use it to streamline their lives and accomplish their goals. So, let's get started and together explore the transformational possibilities of AI. Purpose of The Book and Targeted Audience The book "Introduction to Artificial Intelligence and Generative Ai For Novice aims to give readers an accessible and digestible introduction to the principles of AI. The book tries to demystify the often scary and overwhelming realm of AI and aid readers in developing a deeper grasp of this quickly developing technology.

Building Products with Generative AI Kindle Edition

Building Products with Generative AI Kindle Edition
Author: Anand Vemula
Publisher: Anand Vemula
Total Pages: 61
Release:
Genre: Computers
ISBN:
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"Building Products with Generative AI" explores the transformative potential of generative artificial intelligence (AI) in product development. The book delves into various aspects of generative AI, starting with an introduction to Generative Adversarial Networks (GANs) and their applications in product design. It discusses how GANs can generate realistic design variations, explore novel concepts, and enhance creativity and innovation in the design process. Fundamental principles of product design, including design theories, user-centered design methodologies, and design thinking frameworks, are explored to provide a solid foundation for integrating generative AI into the product development pipeline. The book emphasizes the importance of data preparation and training strategies for generative models, highlighting techniques for data collection, curation, preprocessing, and model training. Design generation techniques such as conditional generation, style transfer, and text-to-image synthesis are examined in detail, showcasing how these techniques can be leveraged to generate customized designs, synthesize new design aesthetics, and translate textual descriptions into visual representations. The book also explores how generative AI can be integrated into collaborative design processes, enabling real-time collaboration, feedback loops, and iterative improvement. It addresses ethical and bias concerns in AI-driven design, emphasizing responsible AI development practices to ensure fairness, transparency, and accountability. Through case studies, the book demonstrates real-world applications of generative AI in designing customizable products, providing personalized recommendations, and automating design tasks. It also discusses emerging trends in generative AI, ethical implications, and technical challenges in implementation. In conclusion, "Building Products with Generative AI" offers a comprehensive overview of how generative AI is revolutionizing product development. It provides practical insights, strategies, and techniques for harnessing the power of generative AI to drive creativity, efficiency, and innovation in product design. The book serves as a valuable resource for designers, engineers, and business leaders seeking to leverage generative AI to create groundbreaking products that meet the evolving needs of consumers in the digital age.