Author: Etienne Noumen
Publisher: Etienne Noumen
ISBN:
Category : Computers
Languages : en
Pages : 249

Get Book Here

Book Description
Dive into the revolutionary world of Artificial Intelligence with 'AI Unraveled: Demystifying Frequently Asked Questions on Artificial Intelligence'. This comprehensive guide is your portal to understanding AI's most intricate concepts and cutting-edge developments. Whether you're a curious beginner or an AI enthusiast, this book is tailored to unveil the complexities of AI in a simple, accessible manner. What's Inside: Fundamental AI Concepts: Journey through the basics of AI, machine learning, deep learning, and neural networks. AI in Action: Explore how AI is reshaping industries and society, diving into its applications in computer vision, natural language processing, and beyond. Ethical AI: Tackle critical issues like AI ethics and bias, understanding the moral implications of AI advancements. Industry Insights: Gain insights into how AI is revolutionizing industries and impacting our daily lives. The Future of AI: Forecast the exciting possibilities and challenges that lie ahead in the AI landscape. Special Focus on Generative AI & LLMs: Latest AI Trends: Stay updated with the latest in AI, including ChatGPT, Google Gemini, GPT-x, Gemini, and more. Interactive Quizzes: Test your knowledge with engaging quizzes on Generative AI and Large Language Models (LLMs). Practical Guides: Master GPT-x with a simplified guide, delve into advanced prompt engineering, and explore the nuances of temperature settings in AI. Real-World Applications: Learn how to leverage AI in various sectors, from healthcare to cybersecurity, and even explore its potential in areas like aging research and brain implants. For the AI Enthusiast: Prompt Engineering: Uncover secrets to crafting effective prompts for ChatGPT/Google Gemini. AI Career Insights: Explore lucrative career paths in AI, including roles like AI Prompt Engineers. AI Investment Guide: Navigate the world of AI stocks and investment opportunities. For AI Developers: How to develop AI-powered apps effectively? Generative AI Technology Stack Overview – A Comprehensive Guide Your Guide to Navigating AI: Do-It-Yourself Tutorials: From building custom ChatGPT applications to running LLMs locally, this book offers step-by-step guides. AI for Everyday Use: Learn how AI can assist in weight loss, social media, and more. 'AI Unraveled' is more than just a book; it's a resource for anyone looking to grasp the complexities of AI and its impact on our world. Get ready to embark on an enlightening journey into the realm of Artificial Intelligence!" More Topics Covered: Artificial Intelligence, Machine Learning, Deep Learning, NLP, AI Ethics, Robotics, Cognitive Computing, ChatGPT, OpenAI, Google Gemini, Generative AI, LLMs, AI in Healthcare, AI Investments, and much more. GPT-x vs Gemini: Pros and Cons Mastering GPT-x: Simplified Guide For everyday Users Advance Prompt Engineering Techniques: [Single Prompt Technique, Zero-Shot and Few-Shot, Zero-Shot and Few-Shot, Generated Knowledge Prompting, EmotionPrompt, Chain of Density (CoD), Chain of Thought (CoT), Validation of LLMs Responses, Chain of Verification (CoVe), Agents - The Frontier of Prompt Engineering, Prompt Chaining vs Agents, Tree of Thought (ToT), ReAct (Reasoning + Act), ReWOO (Reasoning WithOut Observation), Reflexion and Self-Reflection, Guardrails, RAIL (Reliable AI Markup Language), Guardrails AI, NeMo Guardrails] Understanding Temperature in GPT-x: A Guide to AI Probability and Creativity Retrieval-Augmented Generation (RAG) model in the context of Large Language Models (LLMs) like GPT-x Prompt Ideas for ChatGPT/Google Gemini How to Run ChatGPT-like LLMs Locally on Your Computer in 3 Easy Steps ChatGPT Custom Instructions Settings for Power Users Examples of bad and good ChatGPT prompts Top 5 Beginner Mistakes in Prompt Engineering Use ChatGPT like a PRO Prompt template for learning any skill Prompt Engineering for ChatGPT The Future of LLMs in Search What is Explainable AI? Which industries are meant for XAI? ChatGPT Best Tips, Cheat Sheet LLMs Utilize Vector DB for Data Storage The Limitation Technique in Prompt Responses Use ChatGPT to learn new subjects Prompts to proofread anything How to Create a Specialized LLM That Understands Your Custom Data Topics: Artificial Intelligence Education Machine Learning Deep Learning Reinforcement Learning Neural networks Data science AI ethics Deepmind Robotics Natural language processing Intelligent agents Cognitive computing AI Apps AI impact AI Tech ChatGPT Open AI Safe AI Generative AI Discriminative AI Sam Altman Google Gemini NVDIA Large Language Models (LLMs) PALM GPT Explainable AI GPUs AI Stocks AI Podcast Q* AI Certification AI Quiz RAG Context Windows Tokens Ai Agents How to access the AI Unraveled: Djamgatech: https://djamgatech.com/product/ai-unraveled-demystifying-frequently-asked-questions-on-artificial-intelligence-paperback-print-book Google eBook: https://play.google.com/store/books/details?id=oySuEAAAQBAJ Apple eBook: https://books.apple.com/us/book/id6445730691 Etsy: https://www.etsy.com/ca/listing/1617575707/ai-unraveled-demystifying-frequently Audible at Amazon : https://www.audible.com/pd/B0BXMJ7FK5/?source_code=AUDFPWS0223189MWT-BK-ACX0-343437&ref=acx_bty_BK_ACX0_343437_rh_us (Use Promo code: 37YT3B5UYUYZW) Audiobook at Google: https://play.google.com/store/audiobooks/details?id=AQAAAEAihFTEZM

Author: Rowel Atienza
Publisher: Packt Publishing Ltd
ISBN: 178862453X
Category : Computers
Languages : en
Pages : 369

Get Book Here

Book Description
Understanding and coding advanced deep learning algorithms with the most intuitive deep learning library in existence Key Features Explore the most advanced deep learning techniques that drive modern AI results Implement deep neural networks, autoencoders, GANs, VAEs, and deep reinforcement learning A wide study of GANs, including Improved GANs, Cross-Domain GANs, and Disentangled Representation GANs Book DescriptionRecent developments in deep learning, including Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and Deep Reinforcement Learning (DRL) are creating impressive AI results in our news headlines - such as AlphaGo Zero beating world chess champions, and generative AI that can create art paintings that sell for over $400k because they are so human-like. Advanced Deep Learning with Keras is a comprehensive guide to the advanced deep learning techniques available today, so you can create your own cutting-edge AI. Using Keras as an open-source deep learning library, you'll find hands-on projects throughout that show you how to create more effective AI with the latest techniques. The journey begins with an overview of MLPs, CNNs, and RNNs, which are the building blocks for the more advanced techniques in the book. You’ll learn how to implement deep learning models with Keras and TensorFlow 1.x, and move forwards to advanced techniques, as you explore deep neural network architectures, including ResNet and DenseNet, and how to create autoencoders. You then learn all about GANs, and how they can open new levels of AI performance. Next, you’ll get up to speed with how VAEs are implemented, and you’ll see how GANs and VAEs have the generative power to synthesize data that can be extremely convincing to humans - a major stride forward for modern AI. To complete this set of advanced techniques, you'll learn how to implement DRL such as Deep Q-Learning and Policy Gradient Methods, which are critical to many modern results in AI.What you will learn Cutting-edge techniques in human-like AI performance Implement advanced deep learning models using Keras The building blocks for advanced techniques - MLPs, CNNs, and RNNs Deep neural networks – ResNet and DenseNet Autoencoders and Variational Autoencoders (VAEs) Generative Adversarial Networks (GANs) and creative AI techniques Disentangled Representation GANs, and Cross-Domain GANs Deep reinforcement learning methods and implementation Produce industry-standard applications using OpenAI Gym Deep Q-Learning and Policy Gradient Methods Who this book is for Some fluency with Python is assumed. As an advanced book, you'll be familiar with some machine learning approaches, and some practical experience with DL will be helpful. Knowledge of Keras or TensorFlow 1.x is not required but would be helpful.

Author: Josh Kalin
Publisher: Packt Publishing Ltd
ISBN: 1789139589
Category : Computers
Languages : en
Pages : 261

Get Book Here

Book Description
Simplify next-generation deep learning by implementing powerful generative models using Python, TensorFlow and Keras Key FeaturesUnderstand the common architecture of different types of GANsTrain, optimize, and deploy GAN applications using TensorFlow and KerasBuild generative models with real-world data sets, including 2D and 3D dataBook Description 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. What you will learnStructure a GAN architecture in pseudocodeUnderstand the common architecture for each of the GAN models you will buildImplement different GAN architectures in TensorFlow and KerasUse different datasets to enable neural network functionality in GAN modelsCombine different GAN models and learn how to fine-tune themProduce a model that can take 2D images and produce 3D modelsDevelop a GAN to do style transfer with Pix2PixWho this book is for This book is for data scientists, machine learning developers, and deep learning practitioners looking for a quick reference to tackle challenges and tasks in the GAN domain. Familiarity with machine learning concepts and working knowledge of Python programming language will help you get the most out of the book.

Author: Bernard Marr
Publisher: John Wiley & Sons
ISBN: 1119695171
Category : Business & Economics
Languages : en
Pages : 275

Get Book Here

Book Description
WINNER AT THE BUSINESS BOOK AWARDS 2022 - SPECIALIST BUSINESS BOOK CATEGORY. As one of the leading business trends today, extended reality (XR) promises to revolutionize the way consumers experience their encounters with brands and products of all kinds. Top brands from Pepsi and Uber to Boeing and the U.S. Army are creating immersive digital experiences that capture the interest and imaginations of their target markets. In Extended Reality in Practice: 100+ Amazing Ways Virtual, Augmented and Mixed Reality are Changing Business and Society, celebrated futurist, technologist, speaker, and author Bernard Marr delivers a robust and accessible explanation of how all kinds of firms are developing innovative XR solutions to business problems. You’ll discover the new ways that companies are harnessing virtual, augmented, and mixed reality to improve consumers’ perception of their brands. You’ll also find out why there are likely to be no industries that will remain untouched by the use of XR, and why these technologies are popular across the commercial, governmental, and non‐profit spectrums. Perfect for Chief Executive Officers, business owners, leaders, managers, and professionals working in business development, Extended Reality in Practice will also earn a place in the libraries of professionals working within innovation teams seeking an accessible resource on the possibilities and potential created by augmented, virtual, and mixed reality technologies. An insightful exploration of extended reality from a renowned thought leader, technologist, and futurist Extended Reality in Practice: 100+ Amazing Ways Virtual, Augmented and Mixed Reality are Changing Business and Society offers readers a front-row seat to one of the most exciting and impactful business trends to find traction in years. Celebrated futurist and author Bernard Marr walks you through the ins and outs of XR, or extended reality, and how it promises to revolutionize everything from the experience of walking through an airport or shopping mall to grabbing a burger at a fast-food restaurant. Discover insightful and illuminating case studies from businesses and organizations in a variety of industries, including Burger King, BMW, Boeing, and the U.S. Army, and see how they’re turning virtual, mixed, and augmented reality experiences into big wins for their stakeholders. You’ll also find out about how XR can help businesses tackle the problems of lackluster engagement and lukewarm customer loyalty with reinvigorated consumer experiences. Ideal for executives, founders, business leaders and owners, and professionals of all sorts, Extended Reality in Practice is an indispensable guide to an indispensable new technology. The book is the leading resource for anyone seeking a one-stop reference for augmented, virtual, and mixed reality tech and their limitless potential for enterprise.

Author: Kailash Ahirwar
Publisher: Packt Publishing Ltd
ISBN: 1789134196
Category : Mathematics
Languages : en
Pages : 310

Get Book Here

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: Bernard Marr
Publisher: John Wiley & Sons
ISBN: 1119548985
Category : Business & Economics
Languages : en
Pages : 220

Get Book Here

Book Description
Cyber-solutions to real-world business problems Artificial Intelligence in Practice is a fascinating look into how companies use AI and machine learning to solve problems. Presenting 50 case studies of actual situations, this book demonstrates practical applications to issues faced by businesses around the globe. The rapidly evolving field of artificial intelligence has expanded beyond research labs and computer science departments and made its way into the mainstream business environment. Artificial intelligence and machine learning are cited as the most important modern business trends to drive success. It is used in areas ranging from banking and finance to social media and marketing. This technology continues to provide innovative solutions to businesses of all sizes, sectors and industries. This engaging and topical book explores a wide range of cases illustrating how businesses use AI to boost performance, drive efficiency, analyse market preferences and many others. Best-selling author and renowned AI expert Bernard Marr reveals how machine learning technology is transforming the way companies conduct business. This detailed examination provides an overview of each company, describes the specific problem and explains how AI facilitates resolution. Each case study provides a comprehensive overview, including some technical details as well as key learning summaries: Understand how specific business problems are addressed by innovative machine learning methods Explore how current artificial intelligence applications improve performance and increase efficiency in various situations Expand your knowledge of recent AI advancements in technology Gain insight on the future of AI and its increasing role in business and industry Artificial Intelligence in Practice: How 50 Successful Companies Used Artificial Intelligence to Solve Problems is an insightful and informative exploration of the transformative power of technology in 21st century commerce.

Author: Bernard Marr
Publisher: John Wiley & Sons
ISBN: 1119646200
Category : Business & Economics
Languages : en
Pages : 189

Get Book Here

Book Description
***BUSINESS BOOK AWARDS - FINALIST 2021*** Discover how 25 powerful technology trends are transforming 21st century businesses How will the latest technologies transform your business? Future Tech Trends in Practice will give you the knowledge of today’s most important technology trends, and how to take full advantage of them to grow your business. The book presents25 real-world technology trends along with their potential contributions to organisational success. You’ll learn how to integrate existing advancements and plan for those that are on the way. In this book, best-selling author, strategic business advisor, and respected futurist Bernard Marr explains the role of technology in providing innovative businesses solutions for companies of varying sizes and across different industries. He covers wide-ranging trends and provides an overview of how companies are using these new and emerging technologies in practice. You, too, can prepare your company for the potential and power of trending technology by examining these and other areas of innovation described in Future Tech Trends in Practice: Artificial intelligence, including machine and deep learning The Internet of Things and the rise of smart devices Self-driving cars and autonomous drones 3D printing and additive manufacturing Blockchain technology Genomics and gene editing Augmented, virtual and mixed reality When you understand the technology trends that are driving success, now and into the future, you’ll be better positioned to address and solve problems within your organisation.

Author: John Hany
Publisher: Packt Publishing Ltd
ISBN: 1789534283
Category : Computers
Languages : en
Pages : 301

Get Book Here

Book Description
Apply deep learning techniques and neural network methodologies to build, train, and optimize generative network models Key FeaturesImplement GAN architectures to generate images, text, audio, 3D models, and moreUnderstand how GANs work and become an active contributor in the open source communityLearn how to generate photo-realistic images based on text descriptionsBook Description With continuously evolving research and development, Generative Adversarial Networks (GANs) are the next big thing in the field of deep learning. This book highlights the key improvements in GANs over generative models and guides in making the best out of GANs with the help of hands-on examples. This book starts by taking you through the core concepts necessary to understand how each component of a GAN model works. You'll build your first GAN model to understand how generator and discriminator networks function. As you advance, you'll delve into a range of examples and datasets to build a variety of GAN networks using PyTorch functionalities and services, and become well-versed with architectures, training strategies, and evaluation methods for image generation, translation, and restoration. You'll even learn how to apply GAN models to solve problems in areas such as computer vision, multimedia, 3D models, and natural language processing (NLP). The book covers how to overcome the challenges faced while building generative models from scratch. Finally, you'll also discover how to train your GAN models to generate adversarial examples to attack other CNN and GAN models. By the end of this book, you will have learned how to build, train, and optimize next-generation GAN models and use them to solve a variety of real-world problems. What you will learnImplement PyTorch's latest features to ensure efficient model designingGet to grips with the working mechanisms of GAN modelsPerform style transfer between unpaired image collections with CycleGANBuild and train 3D-GANs to generate a point cloud of 3D objectsCreate a range of GAN models to perform various image synthesis operationsUse SEGAN to suppress noise and improve the quality of speech audioWho this book is for This GAN book is for machine learning practitioners and deep learning researchers looking to get hands-on guidance in implementing GAN models using PyTorch. You’ll become familiar with state-of-the-art GAN architectures with the help of real-world examples. Working knowledge of Python programming language is necessary to grasp the concepts covered in this book.

Author: Gary Shapiro
Publisher: HarperCollins
ISBN: 0062890530
Category : Business & Economics
Languages : en
Pages : 326

Get Book Here

Book Description
NATIONAL BESTSELLER Ninja Future is an essential read for businesses and individuals striving to remain competitive in a rapidly evolving world: Gary Shapiro, the president and CEO of the Consumer Technology Association, casts his eye toward the future, charting how the innovative technologies of today will transform not only the way business is done but society itself During his more than three decades at the head of the Consumer Technology Association, Gary Shapiro has witnessed, and been a part of, one of the most extraordinary periods of technological change in human history. Today’s world is almost unrecognizable from that of just a decade or two before: in just a few short years, the internet has already transformed how we access information, purchase goods, get from place to place, and do our jobs. And even greater changes are on the horizon. In Ninja Future, Shapiro explains the evolving technological landscape, breakthroughs underway now and those we can only envision. New innovations such as self-driving vehicles, blockchain, 5G, the Internet of Things, and countless others will forever change the economy as we know it. Shapiro uses case studies to identify companies and countries addressing today’s challenges particularly well—and relates lessons from those that have stumbled. Drawing on the insights he has gleaned as a martial arts black belt, he shows how businesses can move to succeed in today’s turbulent environment by adopting the mindset of “ninjas”—adapting to technological change to capitalize on opportunities at lightning speed.

Author: Debi Prasanna Acharjya
Publisher: Springer Nature
ISBN: 3030758559
Category : Technology & Engineering
Languages : en
Pages : 271

Get Book Here

Book Description
This book comprises theoretical foundations to deep learning, machine learning and computing system, deep learning algorithms, and various deep learning applications. The book discusses significant issues relating to deep learning in data analytics. Further in-depth reading can be done from the detailed bibliography presented at the end of each chapter. Besides, this book's material includes concepts, algorithms, figures, graphs, and tables in guiding researchers through deep learning in data science and its applications for society. Deep learning approaches prevent loss of information and hence enhance the performance of data analysis and learning techniques. It brings up many research issues in the industry and research community to capture and access data effectively. The book provides the conceptual basis of deep learning required to achieve in-depth knowledge in computer and data science. It has been done to make the book more flexible and to stimulate further interest in topics. All these help researchers motivate towards learning and implementing the concepts in real-life applications.