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Artificial Intelligence & Generative AI for Beginners: The Complete Guide
*****This book now comes with a FREE VIDEO ChatGPT for Beginners!*****
Do you want an easy guide to understanding AI?Curious about the hype around generative AI?Looking for ways to use ChatGPT, MidJourney for business & personal gain?If you find yourself nodding in agreement, then this book is exactly for you!
Amazon bestselling author & AI Consultant David M. Patel is going to show you everything you need to know become an expert user of artificial intelligence & generative AI. He is going to lead you step-by-step to discovering the foundations of artificial intelligence, understand how generative models work and how to tap into the full power of AI tools like ChatGPT, DALL-E 3 and MidJourney to skyrocket your productivity and scale yourself exponentially.
In this action-oriented guide , you are going to
In part I – Artificial Intelligence for The Fascinating History of 60+ Years of Breakthroughs5 Major Components of AI You Need to KnowThe 3 Types of Machine Learning & How They DifferWhat Role Data and Algorithms Play in AI (Most People Overlook This)Major Fields of NLP, Computer Vision and Robotics + ApplicationsIn part II – Generative AI - What Generative AI Is and Isn’tThe 9 Types of Generative AI & How They WorkBusiness Ideas with Generative 2 Detailed Case StudiesHow to Build & Develop a Generative AI Model from Scratch4 Essential Tools for Developing Your Own Generative AI ModelIn part HOW TO-GUIDES & Practical How To Use Generative AI for Copywriting, Graphic Design & Video EditingThe 12 Best Generative AI Tools for 2024 (#7-#12 Are Barely Known) 13 HANDS ON-GUIDES - Write Articles & Design images with AI & Build Your Own GPT 5 Ethical Questions & Concerns around Generative that Need AnsweringHow Generative AI Will Transform & Disrupt Healthcare, Media, Education & More50+ Best Generative AI Podcasts, Influencers and Thought Leaders to FollowAnd so much more!"ARTIFICIAL INTELLIGENCE & GENERATIVE AI FOR BEGINNERS" is for anyone who seeks to step into the world of AI, whether you are a complete novice curious about the basics, a professional looking to enhance your toolkit, or even a skeptic wondering what all the fuss is about.Don't miss out on the AI wave – whether it's to boost your career, ignite your creativity, or simply to understand the future unfolding around us. This book is a must-have for anyone ready to explore the potential of AI.
The future of AI is here and now. Be a part of it. Discover, learn, and take action – your AI journey starts with this book. Grab your copy today and begin your transformation into the world of AI!
Amazon bestselling author & AI Consultant David M. Patel is going to show you everything you need to know become an expert user of artificial intelligence & generative AI. He is going to lead you step-by-step to discovering the foundations of artificial intelligence, understand how generative models work and how to tap into the full power of AI tools like ChatGPT, DALL-E 3 and MidJourney to skyrocket your productivity and scale yourself exponentially.
In this action-oriented guide , you are going to
In part I – Artificial Intelligence for The Fascinating History of 60+ Years of Breakthroughs5 Major Components of AI You Need to KnowThe 3 Types of Machine Learning & How They DifferWhat Role Data and Algorithms Play in AI (Most People Overlook This)Major Fields of NLP, Computer Vision and Robotics + ApplicationsIn part II – Generative AI - What Generative AI Is and Isn’tThe 9 Types of Generative AI & How They WorkBusiness Ideas with Generative 2 Detailed Case StudiesHow to Build & Develop a Generative AI Model from Scratch4 Essential Tools for Developing Your Own Generative AI ModelIn part HOW TO-GUIDES & Practical How To Use Generative AI for Copywriting, Graphic Design & Video EditingThe 12 Best Generative AI Tools for 2024 (#7-#12 Are Barely Known) 13 HANDS ON-GUIDES - Write Articles & Design images with AI & Build Your Own GPT 5 Ethical Questions & Concerns around Generative that Need AnsweringHow Generative AI Will Transform & Disrupt Healthcare, Media, Education & More50+ Best Generative AI Podcasts, Influencers and Thought Leaders to FollowAnd so much more!"ARTIFICIAL INTELLIGENCE & GENERATIVE AI FOR BEGINNERS" is for anyone who seeks to step into the world of AI, whether you are a complete novice curious about the basics, a professional looking to enhance your toolkit, or even a skeptic wondering what all the fuss is about.Don't miss out on the AI wave – whether it's to boost your career, ignite your creativity, or simply to understand the future unfolding around us. This book is a must-have for anyone ready to explore the potential of AI.
The future of AI is here and now. Be a part of it. Discover, learn, and take action – your AI journey starts with this book. Grab your copy today and begin your transformation into the world of AI!
248 pages, Kindle Edition
Published June 18, 2023
294 people are currently reading
100 people want to read
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Displaying 1 - 14 of 14 reviews
December 4, 2024
Summary:
AI is revolutionizing how we work, interact, and create. Through advancements in machine learning, neural networks, and generative AI, industries are seeing unprecedented innovation – from personalized healthcare to creative fields like music and design. While these developments are exciting, they also raise ethical concerns regarding data privacy, bias, and responsible use. Ultimately, AI offers enormous potential for positive change, and learning how to harness it will prepare you for the future ahead.
AI is revolutionizing how we work, interact, and create. Through advancements in machine learning, neural networks, and generative AI, industries are seeing unprecedented innovation – from personalized healthcare to creative fields like music and design. While these developments are exciting, they also raise ethical concerns regarding data privacy, bias, and responsible use. Ultimately, AI offers enormous potential for positive change, and learning how to harness it will prepare you for the future ahead.
October 12, 2023
Well written and easy to comprehend book covering AI & Generative AI for those wanting to learn more on the subject. David, the author of this book, goes into detail, starting from the high level and delving to the depths of the inter-workings of AI. Highly recommended read for those getting started and wanting more.
December 5, 2024
David M. Patel’s "Artificial Intelligence & Generative AI for Beginners: The Complete Guide" is an accessible introduction to the rapidly evolving world of artificial intelligence. With a focus on practical applications and foundational concepts, the book demystifies AI for readers of all backgrounds. It opens with a historical overview, charting AI’s evolution from theoretical musings to real-world applications like virtual assistants, autonomous vehicles, and generative tools such as ChatGPT. Patel emphasizes that understanding AI is no longer optional in a world where its transformative impact is felt across industries from healthcare to entertainment.
The book explores the building blocks of AI, including machine learning, neural networks, and data-driven algorithms. Machine learning, the backbone of AI systems, is explained in its three main forms: supervised, unsupervised, and reinforcement learning. Each type is accompanied by relatable examples, such as spam detection, customer segmentation, and self-driving cars. Patel then delves into neural networks, likening them to the human brain’s ability to learn and adapt. Through these networks, AI can process complex tasks like image recognition and language translation, leading to innovations like Convolutional Neural Networks (CNNs) for visual data and Recurrent Neural Networks (RNNs) for sequential data.
A significant portion of the book is devoted to generative AI, which Patel describes as one of the most exciting advancements in artificial intelligence. Unlike traditional AI models focused on classification or prediction, generative AI creates new content, from realistic images to original text and music. Patel explains how models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based architectures like GPT function, offering insights into their revolutionary potential. The section also highlights real-world applications, including personalized healthcare, artistic creation, and drug discovery, showcasing AI’s ability to enhance creativity and efficiency.
Patel introduces readers to the concept of prompt engineering, which he describes as a crucial skill for maximizing the utility of generative AI. By crafting effective prompts, users can guide AI systems to produce desired outcomes, whether for creative projects, professional tasks, or data analysis. Techniques for refining prompts, managing context windows, and iterating requests are presented as practical tools for engaging with AI effectively.
The book does not shy away from addressing the ethical challenges associated with AI’s proliferation. Patel discusses issues like data privacy, algorithmic bias, and the misuse of AI-generated content, including deepfakes. He underscores the importance of responsible AI development and usage, advocating for transparency, accountability, and adherence to ethical guidelines. These considerations are vital as generative AI becomes increasingly integrated into industries and personal lives.
In summary, "Artificial Intelligence & Generative AI for Beginners" is both an educational resource and a call to action. Patel highlights the transformative power of AI across diverse fields while emphasizing the need for informed and ethical engagement. Readers are encouraged to embrace AI not only as a tool for innovation but as a force for positive change. With its clear explanations and practical insights, the book equips readers with the knowledge to navigate and leverage the exciting possibilities of the AI-driven future.
The book explores the building blocks of AI, including machine learning, neural networks, and data-driven algorithms. Machine learning, the backbone of AI systems, is explained in its three main forms: supervised, unsupervised, and reinforcement learning. Each type is accompanied by relatable examples, such as spam detection, customer segmentation, and self-driving cars. Patel then delves into neural networks, likening them to the human brain’s ability to learn and adapt. Through these networks, AI can process complex tasks like image recognition and language translation, leading to innovations like Convolutional Neural Networks (CNNs) for visual data and Recurrent Neural Networks (RNNs) for sequential data.
A significant portion of the book is devoted to generative AI, which Patel describes as one of the most exciting advancements in artificial intelligence. Unlike traditional AI models focused on classification or prediction, generative AI creates new content, from realistic images to original text and music. Patel explains how models like Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer-based architectures like GPT function, offering insights into their revolutionary potential. The section also highlights real-world applications, including personalized healthcare, artistic creation, and drug discovery, showcasing AI’s ability to enhance creativity and efficiency.
Patel introduces readers to the concept of prompt engineering, which he describes as a crucial skill for maximizing the utility of generative AI. By crafting effective prompts, users can guide AI systems to produce desired outcomes, whether for creative projects, professional tasks, or data analysis. Techniques for refining prompts, managing context windows, and iterating requests are presented as practical tools for engaging with AI effectively.
The book does not shy away from addressing the ethical challenges associated with AI’s proliferation. Patel discusses issues like data privacy, algorithmic bias, and the misuse of AI-generated content, including deepfakes. He underscores the importance of responsible AI development and usage, advocating for transparency, accountability, and adherence to ethical guidelines. These considerations are vital as generative AI becomes increasingly integrated into industries and personal lives.
In summary, "Artificial Intelligence & Generative AI for Beginners" is both an educational resource and a call to action. Patel highlights the transformative power of AI across diverse fields while emphasizing the need for informed and ethical engagement. Readers are encouraged to embrace AI not only as a tool for innovation but as a force for positive change. With its clear explanations and practical insights, the book equips readers with the knowledge to navigate and leverage the exciting possibilities of the AI-driven future.
December 4, 2024
bit of an obvious read
Notes:
- AI has become an integral part of daily life, transforming industries such as healthcare, entertainment, and retail.
- at its core, it’s about empowering machines to enhance human intelligence. Essentially, AI systems are designed to learn from data, adapt to new inputs, and make decisions – often faster and more accurately than we can. From virtual assistants like Siri to self-driving cars, AI is becoming a bigger part of everyday life, and it’s reshaping industries like healthcare, finance, and education.
- The journey of AI began in the 1950s with researchers like Alan Turing, who posed the question of whether machines could think. Over the decades, AI evolved from theoretical concepts to real-world applications, with machine learning and deep learning driving incredible advancements.
- Natural Language Processing, or NLP, enables machines to understand and generate human language, allowing for smoother interactions with tools like chatbots or voice assistants. Computer vision allows AI to analyze and interpret visual data, such as recognizing objects in photos or videos. Expert systems simulate human decision-making by following a set of rules, helping solve complex problems in fields like healthcare or finance. Finally, robotics extends AI into the physical world, powering self-driving cars, robotic surgery, and more.
- Data provides the experience AI systems need to learn, while algorithms guide how they process that information and make decisions.
- Supervised learning is the most common type. In this method, systems are trained using labeled data, where input is paired with the correct output.
- Unsupervised learning works without labeled data.
- Reinforcement learning is distinct because it teaches systems to learn by interacting with their environment.
- Deep learning enhances this concept by adding multiple hidden layers to these neural networks, which allows them to identify more complex features and patterns.
- Convolutional Neural Networks – or CNNs – are highly effective for image-related tasks
- Recurrent Neural Networks – shortened to RNNs – on the other hand, are designed for sequential data, making them perfect for tasks like language translation or speech recognition. Unlike traditional models, RNNs retain memory of previous inputs, helping them predict the next step in a sequence.
Notes:
- AI has become an integral part of daily life, transforming industries such as healthcare, entertainment, and retail.
- at its core, it’s about empowering machines to enhance human intelligence. Essentially, AI systems are designed to learn from data, adapt to new inputs, and make decisions – often faster and more accurately than we can. From virtual assistants like Siri to self-driving cars, AI is becoming a bigger part of everyday life, and it’s reshaping industries like healthcare, finance, and education.
- The journey of AI began in the 1950s with researchers like Alan Turing, who posed the question of whether machines could think. Over the decades, AI evolved from theoretical concepts to real-world applications, with machine learning and deep learning driving incredible advancements.
- Natural Language Processing, or NLP, enables machines to understand and generate human language, allowing for smoother interactions with tools like chatbots or voice assistants. Computer vision allows AI to analyze and interpret visual data, such as recognizing objects in photos or videos. Expert systems simulate human decision-making by following a set of rules, helping solve complex problems in fields like healthcare or finance. Finally, robotics extends AI into the physical world, powering self-driving cars, robotic surgery, and more.
- Data provides the experience AI systems need to learn, while algorithms guide how they process that information and make decisions.
- Supervised learning is the most common type. In this method, systems are trained using labeled data, where input is paired with the correct output.
- Unsupervised learning works without labeled data.
- Reinforcement learning is distinct because it teaches systems to learn by interacting with their environment.
- Deep learning enhances this concept by adding multiple hidden layers to these neural networks, which allows them to identify more complex features and patterns.
- Convolutional Neural Networks – or CNNs – are highly effective for image-related tasks
- Recurrent Neural Networks – shortened to RNNs – on the other hand, are designed for sequential data, making them perfect for tasks like language translation or speech recognition. Unlike traditional models, RNNs retain memory of previous inputs, helping them predict the next step in a sequence.
December 26, 2023
The first half of the book better than the second half
The first section of the book was very good in explaining AI. When the author got deeper in GenAI, things started to fall apart. For one thing, the depth of the information was not very deep. Second, it is obvious that GenAI was not used when editing this book. Some section titles were not bold-faced which made it difficult to know when a new section was starting. Next, there is inconsistencies throughout the book. For instance, in describing the different types of GenAI such as Text-to-Text, sometimes it is abbreviated at TTT or T2T. Another example is in the use cases. In one section, Gaming Company U becomes Gaming Company V directly under the title of that section.
These are small issues, but it makes me wonder if GenAI was used. If it was used, how good is it going to be if it made such simple errors in this book.
The first section of the book was very good in explaining AI. When the author got deeper in GenAI, things started to fall apart. For one thing, the depth of the information was not very deep. Second, it is obvious that GenAI was not used when editing this book. Some section titles were not bold-faced which made it difficult to know when a new section was starting. Next, there is inconsistencies throughout the book. For instance, in describing the different types of GenAI such as Text-to-Text, sometimes it is abbreviated at TTT or T2T. Another example is in the use cases. In one section, Gaming Company U becomes Gaming Company V directly under the title of that section.
These are small issues, but it makes me wonder if GenAI was used. If it was used, how good is it going to be if it made such simple errors in this book.
July 8, 2024
comprehensive and practical guide to AI
“Artificial Intelligence & Generative AI for Beginners: The Complete Guide” by David M. Patel is a well-rounded introduction to the world of AI. This 250-page book introduces AI concepts and techniques (ML, LLMs, Neural Nets, etc.) and then offers practical advice for using each approach, along with plenty of practical examples.. I highly recommend it for readers who are seeking to understand the fundamentals of AI and who would benefit from some practical tips on how to use them.
“Artificial Intelligence & Generative AI for Beginners: The Complete Guide” by David M. Patel is a well-rounded introduction to the world of AI. This 250-page book introduces AI concepts and techniques (ML, LLMs, Neural Nets, etc.) and then offers practical advice for using each approach, along with plenty of practical examples.. I highly recommend it for readers who are seeking to understand the fundamentals of AI and who would benefit from some practical tips on how to use them.
May 18, 2024
To nie jest książka, tylko konspekt, a najpewniej streszczenie odpowiedzi chata GPT (styl, dobór wyrazów i struktura tekstu są identyczne, sprawdzałam). Do tego autor miesza wiedzę ekspercką (w bardzo niewielkiej dawce) z irytująco uproszczonymi objaśnieniami, które często osiągają tak wysoki poziom ogólności, że nie tłumaczą niczego.
January 21, 2024
Good Early Intro into AI
There seems to be a lot of topics, areas and components to AI, and navigating this geography is intimidating. This book is nice and concise, and gentle on the technical aspects, a good place to start.
There seems to be a lot of topics, areas and components to AI, and navigating this geography is intimidating. This book is nice and concise, and gentle on the technical aspects, a good place to start.
January 27, 2024
Good information on usage of AI, but don't expect to know the details on how AI works after reading this. Also, hard not to wonder if all or parts of this book itself were created by the author or generative AI, especially when you see chapter numbers like 2.3.1.2.1 :-)
June 9, 2024
Informative and enlightening
David Patel achieves his goal: to introduce his readers to the fascinating world and possibilities of Generative AI. There's more to cover, obviously, but he leaves us wanting for more knowledge on this topic.
David Patel achieves his goal: to introduce his readers to the fascinating world and possibilities of Generative AI. There's more to cover, obviously, but he leaves us wanting for more knowledge on this topic.
July 17, 2024
A quick read that provides a good overview of artificial intelligence, tends, suggestions on how the leverage it in business and day to day life. Author provides an exhaustive list of other resources a reader can look into for continued learning.
February 7, 2024
The author clearly wrote this book using generative AI. Probably spent less time writing it than it takes to read it. If this is the future of books using generative AI, it's not looking very good.
April 21, 2024
It is amazing instructional books for a layman.
December 31, 2024
Well written
Displaying 1 - 14 of 14 reviews