Foundations Of Generative Ai Learn Chatgpt Neural Networks Real World Ai Projects Step By Step
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Foundations Of Generative Ai Learn Chatgpt Neural Networks Real World Ai Projects Step By Step
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Author : Everett Dean Marshall
language : en
Publisher: Gabriel Mensah
Release Date : 2025-07-07
Foundations Of Generative Ai Learn Chatgpt Neural Networks Real World Ai Projects Step By Step written by Everett Dean Marshall and has been published by Gabriel Mensah this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-07 with Computers categories.
🤖 Build Practical AI Skills—From ChatGPT to Neural Networks Looking to master AI but overwhelmed by technical jargon? Foundations of Generative AI strips away complexity and guides you through the essential skills—from ChatGPT and prompt crafting to designing neural networks and deploying projects—with clear, hands-on tutorials for beginners and enthusiasts. 🔍 What You’ll Learn Day by Day How Generative AI Works Understand what generative models are, including GANs, VAEs, and transformers, and how they produce text, images, and audio from scratch. Hands-On ChatGPT & Prompt Engineering Use real examples to write effective prompts, refine ChatGPT outputs, and integrate into real-world applications. Prompts are the bridge to AI creativity. Build and Train Neural Networks Learn the math behind backpropagation, model training, and fine-tuning—from theory to code. Step-by-Step AI Projects Launch three guided projects—including text generation and image synthesis—to turn theory into working AI applications. Inspired by Packt’s practical guides. Responsible AI & Ethics Tackle bias, hallucinations, and safety measures to build AI tools that are reliable, fair, and trustworthy. 🎯 Why This Book Stands Out Designed for First-Timers – No prior AI experience needed. Concepts are explained clearly, without overwhelming jargon. Project-Based Learning – Every chapter includes a working example you can run in minutes. Built for 2025 and Beyond – Covers the latest: GPT‑4, multimodal generators, and current AI toolkits. Insightful & Practical – Combines strong technical foundations with real-world applications and ethical best practices 💡 Benefits You’ll Gain ✅Benefit. 🔥Outcome You'll Achieve Genuine AI Literacy Understand how modern AI models generate content. Hands-On Experience Build and launch real-world AI tools using guided projects. Better AI Interactions. Master prompts to get smarter, practical outputs. Confident Deployment. Safely implement models while avoiding common pitfalls. Tech-Savvy Edge. Stand out with modern AI knowledge and capabilities. 👥 Who This Book is Perfect For Tech beginners seeking a structured and robust AI introduction Developers and professionals aiming to integrate AI into applications Students, creators, and entrepreneurs ready to build or enhance AI-powered tools Ready to start building with AI? Click Add to Cart for Foundations of Generative AI—your step-by-step guide to mastering ChatGPT, neural networks, and real-world AI applications—all without drowning in theory.
Kickstart Artificial Intelligence Fundamentals Master Machine Learning Neural Networks And Deep Learning From Basics To Build Modern Ai Solutions With Python And Tensorflow Keras
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Author : Dr. S.Mahesh
language : en
Publisher: Orange Education Pvt Limited
Release Date : 2025-03-29
Kickstart Artificial Intelligence Fundamentals Master Machine Learning Neural Networks And Deep Learning From Basics To Build Modern Ai Solutions With Python And Tensorflow Keras written by Dr. S.Mahesh and has been published by Orange Education Pvt Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-29 with Computers categories.
Master AI Fundamentals and Build Real-World Machine Learning and Deep Learning Solutions. Key Features● Hands-on AI guide with Python, TensorFlow, and Keras implementations.● Step-by-step walkthroughs of Machine Learning, Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM) models.● Bridges AI theory with real-world applications and coding exercises. Book DescriptionAI is transforming industries, driving innovation, and shaping the future of technology. A strong foundation in AI fundamentals is essential for anyone looking to stay ahead in this rapidly evolving field. Kickstart Artificial Intelligence Fundamentals is a comprehensive companion designed to demystify core AI concepts, covering Machine Learning, Deep Learning, and Neural Networks. Tailored for all AI enthusiasts, this book provides hands-on Python implementation using the TensorFlow-Keras framework, ensuring a seamless learning experience from theory to practice. Bridging the gap between concepts and real-world applications, this book offers intuitive explanations, mathematical foundations, and practical use cases. Readers will explore supervised and unsupervised Machine Learning models, master Convolutional Neural Networks for image classification, and leverage Long Short-Term Memory networks for time-series forecasting. Each chapter includes coding examples and guided exercises, making it an invaluable resource for both beginners and advanced learners. Beyond technical expertise, this book explores emerging trends like Generative AI and ethical considerations in AI, preparing readers for the challenges and opportunities in the field. This book will provide you the essential knowledge and hands-on experience to stay competitive. Don’t get left behind—embrace AI and future-proof your career today! What you will learn● Build and train machine learning models for real-world datasets.● Apply neural networks to classification and regression tasks.● Implement CNNs and LSTMs for vision and sequence modeling.● Solve AI problems using Python, TensorFlow, and Keras.● Fine-tune pre-trained models for domain-specific applications.● Explore generative AI for creative and industrial use cases.
Generative Ai For Beginners Practical Guide To Chatgpt Machine Learning And Ai Applications
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Author : Caleb Morgan Whitaker
language : en
Publisher: Gabriel Mensah
Release Date : 2025-07-07
Generative Ai For Beginners Practical Guide To Chatgpt Machine Learning And Ai Applications written by Caleb Morgan Whitaker and has been published by Gabriel Mensah this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-07 with Computers categories.
🤖 Learn Generative AI — From Zero to Real Projects with Confidence Curious about AI but overwhelmed by technical jargon? Generative AI for Beginners is your clear, hands‑on guide to mastering ChatGPT, neural networks, and practical AI applications—all explained in simple terms for non‑techies and aspiring creators. 🔍 What You’ll Learn & Build Generative AI Simplified Explore how models like GPT‑4, GANs, and VAEs generate text, images, and audio—without getting lost in mathematics. Source: Generative AI for Beginners: A Comprehensive Guide simplifies these concepts for novices. ChatGPT & Prompt Engineering Learn how to design prompts that elicit useful, high‑quality responses for writing, decision‑making, or brainstorming—just like top-rated beginner AI guides. Neural Networks Made Accessible Cover core machine learning ideas like backpropagation, supervised vs. unsupervised learning, and model training using intuitive, non-technical explanations . Practical AI Applications You Can Build Use guided mini‑projects—create a chatbot, prompt‑powered text generator, or image generator—using free and open‑source tools, and gain real hands‑on experience. Ethics & Future Opportunities Understand ethical considerations, bias issues, and emerging Web3/AI trends so you can build responsibly and stay ahead . 🎯 Why This Book Works Beginner-First, Jargon-Free – No prior experience required. Learn at your own pace, with bite‑sized chapters. Project-Based Learning – Each section builds a real AI tool, not just theory—similar to bestsellers that focus on application. Up‑to‑Date for 2025 – Covers current models like GPT‑4, open-source frameworks like Hugging Face, and modern AI applications. Balance of Theory & Practice – Unlike superficial overviews, this guide gives you both understanding and the means to create tangible AI projects. 💡 Your Gains in Action ✅Benefit. 🔥You’ll Be Able To… Understand AI Fundamentals. Clearly explain and use generative AI in daily tasks. Interact Smart with ChatGPT. Create prompts for writing, research, and business needs. Build Real Tools. Deploy your own chatbot, image generator, or text app. Upload & Use Ethical AI. Consider bias, consent, and best practices in your projects. Stay Ahead in AI Trends. Understand LLMs, neural nets, GANs, and future AI paths. 👤 Who Should Read This Beginners eager to start building AI without coding Professionals and students wanting a full AI foundation and skills Creatives and entrepreneurs looking to leverage AI tools in their projects Ready to build useful AI projects in real-time? Tap Add to Cart for Generative AI for Beginners—your step-by-step roadmap to mastering prompt engineering, neural networks, and real-world AI applications by just reading and doing.
Advanced Statistical Methods In Life Science
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Author : Basavarajaiah D.M
language : en
Publisher: CRC Press
Release Date : 2025-07-25
Advanced Statistical Methods In Life Science written by Basavarajaiah D.M and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-25 with Mathematics categories.
This book introduces the principles and foundations of advanced statistical methods for designing experiments and testing hypotheses in life sciences. Advanced statistical methods, such as testing of hypotheses, recent methods of sample size determination/imputation, estimation techniques, probability distributions, and univariate analysis demonstrated with real data, and their integration into life sciences are included in this book. Advanced topics are presented with sufficient conceptual depth and examples to explain the use of recent statistical techniques and to demonstrate what conclusions can be drawn at the right time using modeling in life science research. Key features: Explains the derivation of statistical models to prove disease transmission using massive real-world datasets to explore practical applicability Incorporates the application of innovative advanced statistical and epidemiological models and demonstrates the possible solutions for public health policy intervention Helps to understand the process of hypothesis testing in small or larger observations by using weighted parameters Presents suitable examples and real-life research datasets, and all models can easily be followed in formulating statistical and mathematical derivations and key points Includes machine learning (ML), statistical methods for meta-analysis, testing of hypotheses, methods of imputation, estimation techniques, probability distributions, univariate analysis, and recent nonparametric methods, all illustrated through actual data This textbook is for students and scholars of various courses in life sciences, medicine, mathematics, and statistical science. It will also help academicians and researchers to understand the foundation of this topic.
Examining Cybersecurity Risks Produced By Generative Ai
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Author : Almomani, Ammar
language : en
Publisher: IGI Global
Release Date : 2025-05-01
Examining Cybersecurity Risks Produced By Generative Ai written by Almomani, Ammar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-01 with Computers categories.
As generative artificial intelligence (AI) evolves, it introduces new opportunities across industries, from content creation to problem-solving. However, with these advancements come significant cybersecurity risks that demand closer scrutiny. Generative AI, capable of producing text, images, code, and deepfakes, presents challenges in cybersecurity. Malicious scammers could leverage these technologies to automate cyberattacks, create sophisticated phishing schemes, or bypass traditional security systems with efficiency. This intersection of cutting-edge AI and cybersecurity concerns requires new organizational safeguards for digital environments, highlighting the need for new protocols, regulations, and proactive defense mechanisms to mitigate potential threats. Examining Cybersecurity Risks Produced by Generative AI addresses the intersections of generative AI with cybersecurity, presenting its applications, potential risks, and security frameworks designed to harness its benefits while mitigating challenges. It provides a comprehensive, up-to-date resource on integrating generative models into cybersecurity practice and research. This book covers topics such as deepfakes, smart cities, and phishing attacks, and is a useful resource for computer engineers, security professionals, business owners, policymakers, academicians, researchers, and data scientists.
Textual Intelligence
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Author : Meenakshi Malik
language : en
Publisher: John Wiley & Sons
Release Date : 2025-07-23
Textual Intelligence written by Meenakshi Malik and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-23 with Computers categories.
The book is a must-have resource for anyone looking to understand the complexities of generative AI, offering comprehensive insights into LLMs, effective training strategies, and practical applications. Textual Intelligence: Large Language Models and Their Real-World Applications provides an overview of generative AI and its multifaceted applications, as well as the significance and potential of Large Language Models (LLMs), including GPT and LLaMA. It addresses the generative AI project lifecycle, challenges in existing data architectures, proposed use case planning and scope definition, model deployment, and application integration. Training LLMs, data requirements for effective LLM training, pre-training and fine-tuning processes, and navigating computational resources and infrastructure are also discussed. The volume delves into in-context learning and prompt engineering, offering strategies for crafting effective prompts, techniques for controlling model behavior and output quality, and best practices for prompt engineering. Textual Intelligence: Large Language Models and Their Real-World Applications also discusses cost optimization strategies for LLM training, aligning models to human values, optimizing model architectures, the power of transfer learning and fine-tuning, instruction fine-tuning for precision, and parameter-efficient fine-tuning (PEFT) with adapters such as LoRA, QLoRA, and soft prompts, making it an essential guide for both beginners and industry veterans. Readers will find this book: Explores the real-world potential of large language models; Introduces industry-changing AI solutions; Provides advanced insights on AI and its models. Audience Industry professionals, academics, graduate students, and researchers seeking real-world solutions using generative AI.
Toward Artificial General Intelligence
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Author : Victor Hugo C. de Albuquerque
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2023-11-06
Toward Artificial General Intelligence written by Victor Hugo C. de Albuquerque and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-06 with Computers categories.
Artificial Intelligence (AI) has been an exciting field of study and research in educational institutions and research labs across the globe. Technology giants and IT organizations invest heavily on AI technologies and tools with the aim of preciselyautomating a variety of simple as well as complicated business operations acrossindustry verticals. This book covers the latest trends and transitions happening in thefuturistic AI domain. The book also focuses on machine and deep learning (ML/DL)algorithms, which are, undoubtedly, the mainstream implementation technologies ofstate-of-the-art AI systems and services. Also, there are chapters on computer vision(CV) and natural language processing (NLP), the primary use cases and applicationsof AI. The book has well-written chapters for demystifying AI model engineeringmethods. Further on, our esteemed readers can fi nd details on AI model evaluation,optimization, deployment and observability. Finally, the book deals and describesgenerative AI, the latest buzzword in the IT industry. The book presents the recent ground-breaking changes taking place in the aspects of AI model building, hosting, running and maintaining in cloud environments, articulates and accentuates the most recent developments taking place in the domain of Artifi cial Intelligence, covers the noteworthy innovations and disruptions towards Generative Artificial Intelligence (Generative AI), explains the breakthrough innovations and disruptions towards Artifi cial General Intelligence (AGI) and delineates an engaging discussion of Natural Language Processing, Neuromorphic Systems and Biometrics.
Generative Artificial Intelligence In Finance
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Author : Pethuru Raj Chelliah
language : en
Publisher: John Wiley & Sons
Release Date : 2025-01-22
Generative Artificial Intelligence In Finance written by Pethuru Raj Chelliah and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-22 with Computers categories.
This comprehensive volume delves deep into the diverse applications and implications of generative AI across accounting, finance, economics, business, and management, providing readers with a holistic understanding of this rapidly evolving landscape. Generative Artificial Intelligence in Finance: Large Language Models, Interfaces, and Industry Use Cases to Transform Accounting and Finance Processes provides a comprehensive guide to ethically harnessing generative AI systems to reshape financial management. Generative AI is a key theme across the accounting and finance sectors to drive significant optimizations leading to sustainability. Across 22 chapters, leading researchers supply innovative applications of large language models across the economic realm. Through detailed frameworks, real-world case studies, and governance recommendations, this book highlights applied research for generative AI in finance functions. Several chapters demonstrate how data-driven insights from AI systems can optimize complex financial processes to reduce resource usage, lower costs, and drive positive environmental impact over the long term. In addition, chapters on AI-enabled risk assessment, fraud analytics, and regulatory technology highlight applied research for generative AI in finance. The book also explores emerging applications like leveraging blockchain and metaverse interfaces to create generative AI models that can revolutionize areas from carbon credit trading to virtual audits. Overall, with in-depth applied research at the nexus of sustainability and optimization enabled by data science and generative AI, the book offers a compilation of best practices in leveraging AI for optimal, ethical, and future-oriented financial management. Audience The audience for this book is quite diverse, ranging from financial and accounting experts across banking, insurance, consultancies, regulatory agencies, and corporations seeking to enhance productivity and efficiency; business leaders want to implement ethical and compliant AI practices; researchers exploring the domain of AI and finance.
Demystifying Deep Learning
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Author : Douglas J. Santry
language : en
Publisher: John Wiley & Sons
Release Date : 2023-12-12
Demystifying Deep Learning written by Douglas J. Santry and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-12 with Computers categories.
DEMYSTIFYING DEEP LEARNING Discover how to train Deep Learning models by learning how to build real Deep Learning software libraries and verification software! The study of Deep Learning and Artificial Neural Networks (ANN) is a significant subfield of artificial intelligence (AI) that can be found within numerous fields: medicine, law, financial services, and science, for example. Just as the robot revolution threatened blue-collar jobs in the 1970s, so now the AI revolution promises a new era of productivity for white collar jobs. Important tasks have begun being taken over by ANNs, from disease detection and prevention, to reading and supporting legal contracts, to understanding experimental data, model protein folding, and hurricane modeling. AI is everywhere—on the news, in think tanks, and occupies government policy makers all over the world —and ANNs often provide the backbone for AI. Relying on an informal and succinct approach, Demystifying Deep Learning is a useful tool to learn the necessary steps to implement ANN algorithms by using both a software library applying neural network training and verification software. The volume offers explanations of how real ANNs work, and includes 6 practical examples that demonstrate in real code how to build ANNs and the datasets they need in their implementation, available in open-source to ensure practical usage. This approachable book follows ANN techniques that are used every day as they adapt to natural language processing, image recognition, problem solving, and generative applications. This volume is an important introduction to the field, equipping the reader for more advanced study. Demystifying Deep Learning readers will also find: A volume that emphasizes the importance of classification Discussion of why ANN libraries, such as Tensor Flow and Pytorch, are written in C++ rather than Python Each chapter concludes with a “Projects” page to promote students experimenting with real code A supporting library of software to accompany the book at https://github.com/nom-de-guerre/RANT An approachable explanation of how generative AI, such as generative adversarial networks (GAN), really work. An accessible motivation and elucidation of how transformers, the basis of large language models (LLM) such as ChatGPT, work. Demystifying Deep Learning is ideal for engineers and professionals that need to learn and understand ANNs in their work. It is also a helpful text for advanced undergraduates to get a solid grounding on the topic.
Enterprise Generative Ai Well Architected Framework Patterns
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Author : Suvoraj Biswas
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-04-04
Enterprise Generative Ai Well Architected Framework Patterns written by Suvoraj Biswas and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-04 with Computers categories.
Elevate your AI projects with our course on Enterprise Generative AI using AWS's Well-Architected Framework, paving the way for innovation and efficiency Key Features Learn to secure AI environments Achieve excellence in AI architecture Implement AI with AWS solutions Book DescriptionThe course begins with an insightful introduction to the burgeoning field of Generative AI, laying down a robust framework for understanding its applications within the AWS ecosystem. The course focuses on meticulously detailing the five pillars of the AWS Well-Architected Framework—Operational Excellence, Security, Compliance, Reliability, and Cost Optimization. Each module is crafted to provide you with a comprehensive understanding of these essential areas, integrating Generative AI technologies. You'll learn how to navigate the complexities of securing AI systems, ensuring they comply with legal and regulatory standards, and designing them for unparalleled reliability. Practical sessions on cost optimization strategies for AI projects will empower you to deliver value without compromising on performance or scalability. Furthermore, the course delves into System Architecture Excellence, emphasizing the importance of robust design principles in creating effective Generative AI solutions. The course wraps up by offering a forward-looking perspective on the Common Architectural Pattern for FM/LLM Integration & Adoption within the AWS framework. You'll gain hands-on experience with AWS solutions specifically tailored for Generative AI applications, including Lambda, API Gateway, and DynamoDB, among others.What you will learn Apply Operational Excellence in AI Secure Generative AI implementations Navigate compliance in AI solutions Ensure reliability in AI systems Optimize costs for AI projects Integrate FM/LLM with AWS solutions Who this book is for This course is designed for IT professionals, solutions architects, and DevOps engineers looking to specialize in Generative AI. A foundational understanding of AWS and cloud computing is beneficial.