Large Language Model Crash Course

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Deepseek Crash Course

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Author : Eric Lawson
language : en
Publisher: epubli
Release Date : 2025-08-14

Deepseek Crash Course written by Eric Lawson and has been published by epubli this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-14 with Business & Economics categories.

DeepSeek Crash Course: Unlock the Future of AI Productivity DeepSeek isn't just another AI tool—it's a transformative assistant designed to elevate how you think, create, and build in the digital age. Whether you're a developer, entrepreneur, educator, or creative professional, this book provides the knowledge and strategy you need to master one of the most powerful AI platforms available today. From first-time setup to advanced integration, DeepSeek Crash Course walks you through every step with clarity and depth. Learn how to harness the system's full potential for coding, writing, research, collaboration, and beyond. You won't just understand how it works—you'll learn how to make it work for you. Inside This Book, You'll Discover: Prompt Engineering Essentials for DeepSeek Using DeepSeek for Text Generation Code with Confidence: DeepSeek for Programming Help Mastering Chat-Based Interactions with DeepSeek Multimodal Magic: Working with Text and Images Fine-Tuning and Customization: Make DeepSeek Yours Best Practices for Reliable Outputs Each chapter is packed with real-world insights, practical applications, and ethical considerations to help you navigate the evolving AI landscape with skill and confidence. Whether you're solving problems, generating content, or integrating DeepSeek into your daily workflow, this guide gives you the tools to succeed—responsibly and creatively. Scroll Up and Grab Your Copy Today!

Developing Ai Applications With Large Language Models

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Author : Maria Johnsen
language : en
Publisher: Maria Johnsen
Release Date : 2025-01-18

Developing Ai Applications With Large Language Models written by Maria Johnsen and has been published by Maria Johnsen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-18 with Computers categories.

In my previous book Large Language Models (LLms), I explained and discussed about the intricacies of Large Language Models (LLMs), giving readers a comprehensive understanding of these powerful technologies. This book takes that knowledge a step further, focusing on the practical side of developing AI applications using LLMs. It is designed to be a hands-on, step-by-step guide to building AI solutions. Over the years, I’ve been fascinated by the many possibilities AI offers, and I’ve come to realize that many people, from developers to researchers, want to build real-world applications but often don’t know where to start. That’s why I decided to write this book because I believe that with the right guidance, anyone can harness the full potential of LLMs to create meaningful and impactful AI-driven solutions. My book covers a wide range of practical applications, including in industries like healthcare, film production, music, video, and language translation. I also explore how AI can empower researchers and innovators in countless fields. By breaking down complex topics such as tokenization, attention mechanisms, and transformer architecture in an approachable way, I want to help you understand these essential concepts and how to apply them to build your own AI applications. Throughout this journey, you’ll learn not just how to set up your development environment and choose the right models, but also how to use the most powerful tools available to create applications like chatbots, virtual assistants, and much more. I’ve made sure to emphasize key aspects such as prompt engineering, fine-tuning pretrained models, and adapting LLMs to industries such as healthcare and finance, where they can make the most significant impact. But this book isn’t just about building great technology. It’s also about building responsible technology. I’ve dedicated a section to the ethical challenges that come with working in AI, such as bias and fairness, and I offer strategies for developing scalable AI applications that are both effective and ethical. The motivation behind writing this book is simple: I want to empower you to unlock the potential of LLMs in practical ways. I’ve had the privilege of exploring and developing with AI over the years, and I want to share that experience with you. Whether you’re a developer looking to expand your skills, a researcher trying to integrate AI into your work, or an entrepreneur hoping to revolutionize an industry, this book is meant to be your guide. This book is for anyone eager to explore the practical development of AI applications using Large Language Models. Whether you’re just getting started with AI or looking to enhance your skills, you’ll find something here that speaks to you. It’s particularly suited for: Developers who want to dive deeper into building AI applications, from chatbots to complex AI systems. Researchers who are looking to integrate LLMs into their projects for tasks like data analysis, language translation, or summarization. Industry professionals in fields like healthcare, finance, and entertainment who want to leverage AI to innovate and enhance their business. AI enthusiasts and students who are passionate about AI and want to build practical, real-world applications. By the end of this book, my hope is that you’ll feel confident not only in your understanding of how LLMs work, but also in your ability to apply them to create powerful, responsible AI applications across many different domains.

Large Language Models For Developers

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Author : Oswald Campesato
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-12-26

Large Language Models For Developers written by Oswald Campesato 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 2024-12-26 with Computers categories.

This book offers a thorough exploration of Large Language Models (LLMs), guiding developers through the evolving landscape of generative AI and equipping them with the skills to utilize LLMs in practical applications. Designed for developers with a foundational understanding of machine learning, this book covers essential topics such as prompt engineering techniques, fine-tuning methods, attention mechanisms, and quantization strategies to optimize and deploy LLMs. Beginning with an introduction to generative AI, the book explains distinctions between conversational AI and generative models like GPT-4 and BERT, laying the groundwork for prompt engineering (Chapters 2 and 3). Some of the LLMs that are used for generating completions to prompts include Llama-3.1 405B, Llama 3, GPT-4o, Claude 3, Google Gemini, and Meta AI. Readers learn the art of creating effective prompts, covering advanced methods like Chain of Thought (CoT) and Tree of Thought prompts. As the book progresses, it details fine-tuning techniques (Chapters 5 and 6), demonstrating how to customize LLMs for specific tasks through methods like LoRA and QLoRA, and includes Python code samples for hands-on learning. Readers are also introduced to the transformer architecture’s attention mechanism (Chapter 8), with step-by-step guidance on implementing self-attention layers. For developers aiming to optimize LLM performance, the book concludes with quantization techniques (Chapters 9 and 10), exploring strategies like dynamic quantization and probabilistic quantization, which help reduce model size without sacrificing performance. FEATURES • Covers the full lifecycle of working with LLMs, from model selection to deployment • Includes code samples using practical Python code for implementing prompt engineering, fine-tuning, and quantization • Teaches readers to enhance model efficiency with advanced optimization techniques • Includes companion files with code and images -- available from the publisher

Large Language Model Crash Course

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Author : Jamie Flux
language : en
Publisher: Independently Published
Release Date : 2024-11-11

Large Language Model Crash Course written by Jamie Flux and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-11 with Computers categories.

Unlock the full potential of Natural Language Processing (NLP) with the definitive guide to Large Language Models (LLMs)! This comprehensive resource is perfect for beginners and seasoned professionals alike, revealing the intricacies of state-of-the-art NLP models. Dive into a wealth of knowledge packed with theoretical insights, practical examples, and Python code to implement key concepts. Experience firsthand the transformative power LLMs can have on a variety of applications spanning diverse industries. Key Features: Comprehensive coverage-from foundational NLP concepts to advanced model architectures. Detailed exploration of pre-training, fine-tuning, and deploying LLMs. Hands-on Python code examples for each chapter. SEO-optimized knowledge that encompasses a wide array of tasks and capabilities in NLP. What You Will Learn: Grasp the basics with an introduction to Large Language Models and their influence on NLP. Delve into the essentials of NLP fundamentals critical for LLM comprehension. Analyze traditional language models, including their mechanisms and limitations. Discover the power of word embeddings such as Word2Vec and GloVe. Explore how deep learning catalyzed a revolution in natural language processing. Understand the structure and functionality of neural networks relevant to NLP. Master Recurrent Neural Networks (RNNs) and their applications in text processing. Navigate the workings of Long Short-Term Memory (LSTM) networks for long-term text dependencies. Appreciate the transformative impact of the Transformer architecture on NLP. Learn the importance of attention mechanisms and self-attention in modern LLMs. Decode the architecture and function of the BERT model in NLP tasks. Trace the evolution and design of GPT models from GPT to GPT-4. Explore pre-training methodologies that underpin large-scale language models. Fine-tune LLMs for specific applications with precision and effectiveness. Innovate with generative model fine-tuning for creative text generation tasks. Optimize models through contrastive learning for superior performance. Excavate the nuances of in-context learning techniques in LLMs. Apply transfer learning principles to enhance language model capabilities. Comprehend the nuances of training LLMs from a technical standpoint. Prepare datasets meticulously for language model training success.

Machine Learning Crash Course For Engineers

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Author : Eklas Hossain
language : en
Publisher: Springer Nature
Release Date : 2023-12-26

Machine Learning Crash Course For Engineers written by Eklas Hossain and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-26 with Mathematics categories.

​Machine Learning Crash Course for Engineers is a reader-friendly introductory guide to machine learning algorithms and techniques for students, engineers, and other busy technical professionals. The book focuses on the application aspects of machine learning, progressing from the basics to advanced topics systematically from theory to applications and worked-out Python programming examples. It offers highly illustrated, step-by-step demonstrations that allow readers to implement machine learning models to solve real-world problems. This powerful tutorial is an excellent resource for those who need to acquire a solid foundational understanding of machine learning quickly.

Crash Course Medical Ethics And Medical Law E Book

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Author : William Brooks
language : en
Publisher: Elsevier Health Sciences
Release Date : 2025-04-24

Crash Course Medical Ethics And Medical Law E Book written by William Brooks and has been published by Elsevier Health Sciences this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-24 with Medical categories.

Crash Course – your effective every-day study companion PLUS the perfect antidote for exam stress! Save time and be assured you have the essential information you need in one place to excel on your course and achieve exam success.A winning formula now for over 25 years, having sold over 1 million copies and translated in over 8 languages, each series volume has been fine-tuned and fully updated to make your life easier. Especially written by senior students or junior doctors/residents – those who understand what is essential for exam success – with all information thoroughly checked and quality assured by expert Faculty Advisers, the result is books that exactly meet your needs and you know you can trust.Text boxes help you get to the hints, tips and key points you need fast! A fully revised self-assessment section matching the latest exam formats is included to check your understanding and aid exam preparation.Series volumes have been honed to meet the requirements of today's medical students, although the range of other health students and professionals who need rapid access to the essentials of medical ethics and medical law will also love the unique approach of Crash Course. Whether you need to get out of a fix or aim for a distinction Crash Course is for you!This fully updated, concise textbook on medical ethics and law is perfect for aspiring medical students, current undergraduates, and practicing professionals alike, it offers a comprehensive yet accessible overview of contemporary ethical principles and legal frameworks. Packed with the latest UK guidelines and illuminating case studies, this essential resource equips you to understand and navigate complex clinical dilemmas. From patient consent and confidentiality to end-of-life decisions and public health ethics, gain invaluable insights that will serve you throughout your medical career. Whether you're preparing for university interviews, tackling course material, or refining your professional practice, this textbook provides the knowledge you need to approach medical ethics and law with clarity and competence. - Prepare with confidence, fully covering the core syllabus - Updated self-assessment section matching the latest exam formats – confirm your understanding and improve exam technique fast - All Crash Course indexes and ToCs will be mapped against the UKMLA - Feature boxes will include mnemonics where appropriate

Large Language Model Based Solutions

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Author : Shreyas Subramanian
language : en
Publisher: John Wiley & Sons
Release Date : 2024-04-02

Large Language Model Based Solutions written by Shreyas Subramanian 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 2024-04-02 with Computers categories.

Learn to build cost-effective apps using Large Language Models In Large Language Model-Based Solutions: How to Deliver Value with Cost-Effective Generative AI Applications, Principal Data Scientist at Amazon Web Services, Shreyas Subramanian, delivers a practical guide for developers and data scientists who wish to build and deploy cost-effective large language model (LLM)-based solutions. In the book, you'll find coverage of a wide range of key topics, including how to select a model, pre- and post-processing of data, prompt engineering, and instruction fine tuning. The author sheds light on techniques for optimizing inference, like model quantization and pruning, as well as different and affordable architectures for typical generative AI (GenAI) applications, including search systems, agent assists, and autonomous agents. You'll also find: Effective strategies to address the challenge of the high computational cost associated with LLMs Assistance with the complexities of building and deploying affordable generative AI apps, including tuning and inference techniques Selection criteria for choosing a model, with particular consideration given to compact, nimble, and domain-specific models Perfect for developers and data scientists interested in deploying foundational models, or business leaders planning to scale out their use of GenAI, Large Language Model-Based Solutions will also benefit project leaders and managers, technical support staff, and administrators with an interest or stake in the subject.

From Idea To Bestseller

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Author : David West
language : en
Publisher: Pickle Publishing
Release Date : 2025-07-05

From Idea To Bestseller written by David West and has been published by Pickle Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-05 with Computers categories.

From Idea to Bestseller: Writing Your Book with AI is the ultimate AI book writing guide that shows you how to harness the power of writing with AI tools like ChatGPT, GPT-4, Claude, and Sudowrite. Whether you want to learn how to write a book with ChatGPT or use advanced AI writing tools to speed up your process, this book is designed for authors at every level. ​​​​​​​This comprehensive book writing guide teaches you how to: Generate and validate fresh book ideas using AI Outline your book effectively, including how to outline a book with AI Write compelling fiction or nonfiction manuscripts with AI assistance Master nonfiction book writing with AI techniques and storytelling Edit, revise, and polish your drafts with AI-powered tools Navigate self-publishing with AI and get your book out to readers Market your book using smart book marketing with AI strategies You’ll find practical steps for how to write and publish a book using AI, including tips for writing a novel with ChatGPT, using AI for research, formatting, and creating engaging content that resonates. This book also explores AI ethics, copyright, and the evolving role of AI as your creative partner. Whether you're a fiction author, nonfiction expert, entrepreneur, or educator, From Idea to Bestseller empowers you to confidently use the best AI tools for writers and the GPT-4 writing assistant to bring your book from concept to bestseller.

Communicative Ai

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Author : Mark Coeckelbergh
language : en
Publisher: John Wiley & Sons
Release Date : 2025-04-17

Communicative Ai written by Mark Coeckelbergh 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 2025-04-17 with Social Science categories.

Large Language Models (LLMs), like OpenAI’s ChatGPT and Google’s LaMDA, are not only the most disruptive and controversial technologies of our time, but also offer an unprecedented opportunity to examine human cognition and philosophically question the very nature of language, communication, and intelligence. What is consciousness? What is language? Are LLMs authors? Are LLMs the end of writing as we know it? In Communicative AI, Mark Coeckelbergh and David J. Gunkel offer a critical introduction to LLMs, investigating the philosophical significance of this technology and its practical ramifications. Mobilizing resources from contemporary philosophy, history of ideas, linguistics, and communication theory, the book invites us to re-think some long-standing philosophical issues concerning language, consciousness, truth, authorship, and writing. Through a blend of theoretical analysis, accessible explanations, and practical examples, the book provides readers with a comprehensive overview of the role that this powerful new technology is already playing in our lives. This is a must-read for students and scholars across the humanities and the social sciences, as well as for anyone intrigued by the intersection of technology, language, and human thought.

Transforming Conversational Ai

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Author : Michael McTear
language : en
Publisher: Springer Nature
Release Date : 2024-02-24

Transforming Conversational Ai written by Michael McTear and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-24 with Business & Economics categories.

Acquire the knowledge needed to work effectively in conversational artificial intelligence (AI) and understand the opportunities and threats it can potentially bring. This book will help you navigate from the traditional world of dialogue systems that revolve around hard coded scripts, to the world of large language models, prompt engineering, conversational AI platforms, multi-modality, and ultimately autonomous agents. In this new world, decisions are made by a system that may forever remain a ‘black box’ for most of us. This book aims to eliminate unnecessary noise and describe the fundamental components of conversational AI. Past experiences will prove invaluable in constructing seamless hybrid systems. This book will provide the most recommended solutions, recognizing that it is not always necessary to blindly pursue new tools. Written in unprecedented and turbulent times for conversational interfaces you’ll see that despite previous waves of advancement in conversational technology, now conversational interfaces are gaining unparalleled popularity. Specifically, the release of ChatGPT in November 2022 by Open AI revolutionized the conversational paradigm and showed how easy and intuitive communication with a computer can be. Old professions are being disrupted, new professions are emerging, and even the most conservative corporations are changing their strategy and experimenting with large language models, allocating an unprecedented amount of budget to these projects. No one knows for sure the exact future of conversational AI, but everyone agrees that it’s here to stay. What You'll Learn See how large language models are constructed and used in conversational systems Review the risks and challenges of new technologies in conversational AI Examine techniques for prompt engineering Enable practitioners to keep abreast of recent developments in conversational AI Who This Book Is For Conversation designers, product owners, and product or project managers in conversational AI who wish to learn about new methods and challenges posed by the recent emergence in the public domain of ChatGPT. Data scientists, final year undergraduates and graduates of computer science