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A Systemic Functional Grammar of French: A Simple Introdution
A Systemic Functional Grammar of French provides an accessible introduction to systemic functional linguistics through French.
This concise introduction to the systemic functional grammar (SFG) framework provides illustrations throughout that highlight how the framework can be used to analyse authentic language texts.
This will be of interest to students in alternative linguistic frameworks who wish to acquire a basic understanding of SFG as well as academics in related areas, such as literary and cultural studies, interested in seeing how SFG can be applied to their fields.
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AI Agents in Action
In AI Agents in Action, you’ll learn how to build production-ready assistants, multi-agent systems, and behavioral agents. You’ll master the essential parts of an agent, including retrieval-augmented knowledge and memory, while you create multi-agent applications that can use software tools, plan tasks autonomously, and learn from experience. As you explore the many interesting examples, you’ll work with state-of-the-art tools like OpenAI Assistants API, GPT Nexus, LangChain, Prompt Flow, AutoGen, and CrewAI.
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AI engineering : building applications with foundation models
Foundation models have enabled many new AI use cases while lowering the barriers to entry for building AI products. This has transformed AI from an esoteric discipline into a powerful development tool that anyone can use -- including those with no prior AI experience. In this accessible guide, author Chip Huyen discusses AI engineering: the process of building applications with readily available foundation models, datasets, evaluation benchmarks, and the seemingly infinite number of application patterns. The book also introduces a practical framework for developing an AI application and efficiently deploying it.
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Bringing the forest school approach to your early years practice
This easy-to-read series provides an introduction to some of the most important early years philosophies and shows how they can be incorporated into your setting. Each book provides:an outline of the background to the approachclear explanations of the relevance to contemporary thinkingsuggestions to help you plan a successful learning environmentexamples of what the individual approach can look like in practice.These convenient guides are essential to early years practitioners, students and parents who wish to fully understand what each approach means to their setting and children.How has Forest School helped to change attitudes about risk and challenge in the early years? What are the benefits of using this approach for children's development, health and overall wellbeing? Bringing the Forest School Approach to your Early Years Practice provides an accessible introduction to Forest School practice. It identifies the key issues involved in setting up, running and managing a Forest school environment and offers clear guidance on resources, staffing and space required for successful play and learning outdoors. Including links to the Early Years Foundation Stage and a wide range of case studies, the book covers:The beginnings of Forest School and how practice has developed Child centred play and learning that allows for risk taking and challenge Planning for children's individual needs, learning styles and schemas The learning environment The role of the adult including health and safety and children's welfare.Full of practical advice, this convenient guide will help practitioners to deliver new, exciting and inspiring opportunities for the children they care for
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Build a large language model (from scratch)
Build a Large Language Model (From Scratch) is a practical and eminently-satisfying hands-on journey into the foundations of generative AI. Without relying on any existing LLM libraries, you'll code a base model, evolve it into a text classifier, and ultimately create a chatbot that can follow your conversational instructions. And you'll really understand it because you built it yourself!
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Building Agentic AI Systems: Create intelligent, autonomous AI agents that can reason, plan, and adapt
Gain unparalleled insights into the future of AI autonomy with this comprehensive guide to designing and deploying autonomous AI agents that leverage generative AI (GenAI) to plan, reason, and act. Written by industry-leading AI architects and recognized experts shaping global AI standards and building real-world enterprise AI solutions, it explores the fundamentals of agentic systems, detailing how AI agents operate independently, make decisions, and leverage tools to accomplish complex tasks.
Starting with the foundations of GenAI and agentic architectures, you’ll explore decision-making frameworks, self-improvement mechanisms, and adaptability. The book covers advanced design techniques, such as multi-step planning, tool integration, and the coordinator, worker, and delegator approach for scalable AI agents.
Beyond design, it addresses critical aspects of trust, safety, and ethics, ensuring AI systems align with human values and operate transparently. Real-world applications illustrate how agentic AI transforms industries such as automation, finance, and healthcare. With deep insights into AI frameworks, prompt engineering, and multi-agent collaboration, this book equips you to build next-generation adaptive, scalable AI agents that go beyond simple task execution and act with minimal human intervention.
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Building AI-powered products : The essential guide to AI and GenAI product management
Drawing from her experience at Google and Meta, Dr. Marily Nika delivers the definitive guide for product managers building AI and GenAI powered products. Packed with smart strategies, actionable tools, and real-world examples, this book breaks down the complex world of AI agents and generative AI products into a playbook for driving innovation to help product leaders bridge the gap between niche AI and GenAI technologies and user pain points. Whether you're already leading product teams or are an aspiring product manager, and regardless of your prior knowledge with AI, this guide will empower you to confidently navigate every stage of the AI product lifecycle
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Building Applications with AI Agents: Designing and Implementing Multi-Agent Systems
Generative AI has revolutionized how organizations tackle problems, accelerating the journey from concept to prototype to solution. While these applications enhance efficiency, they often require extensive planning, drafting, and revising to complete complex tasks. By combining many of these actions, AI agents offer greater autonomy and efficiency, but understanding and deploying them remains a challenge for many organizations, especially as technology and research rapidly develops.
This book is your indispensable guide through this intricate and fast-moving landscape. Author Michael Albada provides a practical and research-based approach to designing and implementing single- and multi-agent systems. It simplifies the complexities and equips you with the tools to move from concept to solution efficiently. By the end, you'll:
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Building LLM Powered Applications: Create intelligent apps and agents with large language models
Building LLM Powered Applications delves into the fundamental concepts, cutting-edge technologies, and practical applications that LLMs offer, ultimately paving the way for the emergence of large foundation models (LFMs) that extend the boundaries of AI capabilities.
The book begins with an in-depth introduction to LLMs. We then explore various mainstream architectural frameworks, including both proprietary models (GPT 3.5/4) and open-source models (Falcon LLM), and analyze their unique strengths and differences. Moving ahead, with a focus on the Python-based, lightweight framework called LangChain, we guide you through the process of creating intelligent agents capable of retrieving information from unstructured data and engaging with structured data using LLMs and powerful toolkits. Furthermore, the book ventures into the realm of LFMs, which transcend language modeling to encompass various AI tasks and modalities, such as vision and audio.
Whether you are a seasoned AI expert or a newcomer to the field, this book is your roadmap to unlock the full potential of LLMs and forge a new era of intelligent machines.
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Computer Science Education: Perspectives on Teaching and Learning in School
Drawing together the most up-to-date research from experts all across the world, the second edition of Computer Science Education offers the most up-to-date coverage available on this developing subject, ideal for building confidence of new pre-service and in-service educators teaching a new discipline. It provides an international overview of key concepts, pedagogical approaches and assessment practices.
Highlights of the second edition include:
- New sections on machine learning and data-driven (epistemic) programming
- A new focus on equity and inclusion in computer science education
- Chapters updated throughout, including a revised chapter on relating ethical and societal aspects to knowledge-rich aspects of computer science education
- A new set of chapters on the learning of programming, including design, pedagogy and misconceptions
- A chapter on the way we use language in the computer science classroom.
The book is structured to support the reader with chapter outlines, synopses and key points. Explanations of key concepts, real-life examples and reflective points keep the theory grounded in classroom practice.
The book is accompanied by a companion website, including online summaries for each chapter, 3-minute video summaries by each author and an archived chapter on taxonomies and competencies from the first edition.
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Deep learning for coders with fastai and PyTorch : AI applications without a PhD
Deep learning has the reputation as an exclusive domain for math PhDs. Not so. With this book, programmers comfortable with Python will learn how to get started with deep learning right away. Using PyTorch and the fastai deep learning library, you'll learn how to train a model to accomplish a wide range of tasks-including computer vision, natural language processing, tabular data, and generative networks. At the same time, you'll dig progressively into deep learning theory so that by the end of the book you'll have a complete understanding of the math behind the library's functions
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Discours et analyse du discours
Dans le monde entier, les travaux qui se réclament du « discours » ont envahi l’ensemble des sciences humaines et sociales et des humanités. À quelque discipline qu’ils appartiennent, ceux qui aujourd’hui sont amenés à étudier des textes écrits ou oraux ont besoin de comprendre les enjeux de l’analyse du discours et les ressources qu’elle propose.
Cet ouvrage veut aider les étudiants à appréhender ses présupposés majeurs et les grandes divisions qui le structurent, à comprendre comment les analystes du discours élaborent leurs objets à l’aide de catégories comme genre, type de discours, formation discursive... Ils pourront également prendre la mesure de la diversité des modes de manifestation du discours : de la banale conversation entre amis à la philosophie, des interactions orales aux écrans d’ordinateur, car l’univers du discours dans lequel nous construisons nos identités et donnons sens à nos activités apparaît profondément hétérogène.
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E-learning and the science of instruction : $b proven guidelines for consumers and designers of multimedia learning
This edition includes 3 new chapters focused on evidence regarding signaling in e-Learning, video-based instruction, and immersive virtual reality platforms. The 21 chapters summarized in the table that follows are grouped into five sections. You may choose to read the chapters in order or if you have special interests such as evidence on online games or immersive virtual reality, you can jump to those chapters. Chapters 1-3 summarize foundational concepts that form the base for the rest of the book including the science of learning and basics of experimental evidence. We recommend you start with these chapters. In Section 2, we offer 6 chapters with guidelines and evidence regarding optimal use of visuals, text, and audio in e-learning. Evidence on how to promote productive engagement in e-learning is the focus of Section 3. Section 4 includes 2 chapters relevant to organizational decisions you can make in design and sequencing of lessons and courses. We review social cues in e-learning in Section 5 including personalization of your lessons and ways to promote productive collaborative learning. Section 6 includes 4 chapters highlighting evidence on special applications of digital learning including simulations, games, video-based instruction, and immersive platforms. Chapter 21 includes a checklist that summarizes all of the guidelines presented throughout the book. That is a good place to help you put together all you have learned
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Etudier la publicité
Alors que la publicité ne cesse d'attirer l'attention des journalistes, commentateurs et essayistes qui débattent de son pouvoir manipulateur et de son caractère idéologique, cet ouvrage fournit aux professionnels comme aux étudiants des repères pour aborder l'étude de la publicité en tant que question de société. Il dresse, des années 1950 à aujourd'hui, une synthèse claire des approches théoriques et méthodologiques et des questionnements abordés dans l'étude des discours et des pratiques publicitaires. Il donne des clés pour explorer les enjeux actuels (économiques, sociaux, culturels et politiques) de la publicité et montre les éclairages apportés par les Sciences de l'information et de la communication.
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Évaluation et didactique
La problématique de l’évaluation scolaire a suscité nombre d’études et de recherches depuis les années 1970, tant dans la recherche spécialisée en évaluation qu’en didactique. Tout au long de ces décennies, les apports et points de vue de ces deux domaines ont été ponctuellement croisés, interrogés, débattus. Mais après un demi-siècle de travaux plus ou moins partagés, qu’en est-il de ces approches de l’évaluation scolaire, de leurs spécificités et de leurs convergences ? Quels regards portent-elles l’une sur l’autre ? Quelles sont les tensions que ce dialogue théorique produit ? C’est à de telles questions que cet ouvrage s’intéresse à partir d’une discussion critique de travaux emblématiques en évaluation et en didactique du français et des mathématiques. Ces analyses conduisent à une proposition d’approche théorique de l’évaluation centrée sur l’étude des problèmes spécifiques que posent les contenus et disciplines d’enseignement aux évaluations ; plus particulièrement aux évaluations qui sont présentées, sur un plan institutionnel ou théorique, comme des modèles de référence.
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Guide to Teaching Computer Science: An Activity-Based Approach
This concise yet thorough textbook presents an active-learning model for the teaching of computer science. Offering both a conceptual framework and detailed implementation guidelines, the work is designed to support a Methods of Teaching Computer Science (MTCS) course, but may be applied to the teaching of any area of computer science at any level, from elementary school to university. This text is not limited to any specific curriculum or programming language, but instead suggests various options for lesson and syllabus organization.
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Handbook of artificial intelligence in education
Gathering insightful and stimulating contributions from leading global experts in Artificial Intelligence in Education (AIED), this comprehensive Handbook traces the development of AIED from its early foundations in the 1970s to the present day. The Handbook evaluates the use of AI techniques such as modelling in closed and open domains, machine learning, analytics, language understanding and production to create systems aimed at helping learners, teachers, and educational administrators. Chapters examine theories of affect, metacognition and pedagogy applied in AIED systems; foundational aspects of AIED architecture, design, authoring and evaluation; and collaborative learning, the use of games and psychomotor learning. It concludes with a critical discussion of the wider context of Artificial Intelligence in Education, examining its commercialisation, social and political role, and the ethics of its systems, as well as reviewing the possible challenges and opportunities for AIED in the next 20 years. Providing a broad yet detailed account of the current field of Artificial Intelligence in Education, researchers and advanced students of education technology, innovation policy, and university management will benefit from this thought-provoking Handbook. Chapters will also be useful to support undergraduate courses in AI, computer science, and education
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Hands-on large language models : language understanding and generation
AI has acquired startling new language capabilities in just the past few years. Driven by rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend is enabling new features, products, and entire industries. Through his book's visually educational nature, readers will learn practical tools and concepts they need to use these capabilities today. You'll understand how to use pretrained language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; and use existing libraries and pretrained models for text classification, search, and clusterings. This book also helps you: Understand the architecture of transformer language models that excel at text generation and representation ; Build advanced LLM pipelines to cluster text documents and explore the topics they cover ; Build semantic search engines that go beyond keyword search, using methods like dense retrieval and rerankers ; Explore how generative models can be used, from prompt engineering all the way to retrieval-augmented generation ; Gain a deeper understanding of how to train LLMs and optimize them for specific applications using generative model fine-tuning, contrastive fine-tuning, and in-context learning.
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Hands-on machine learning with Scikit-Learn, Keras and TensorFlow : Concepts, tools, and techniques to build intelligent systems
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurelien Geron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started
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Integrating educational technology into teaching : transforming learning across disciplines
This book continues to help in developing teachers as technology leaders, prioritizing transformative technology integration in the classroom, emphasizing unique affordances of technology for twelve content-area disciplines, and positioning all practices in relation to contemporary educational research perspectives. This edition also launches keen attention to the current issues of digital inequity in our society that influence children's educational success