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Zooarchaeology is the study of animal remains excavated from archaeological sites. The goal of zooarchaeology is to understand human relationships with the environment through their interactions with nonhuman animals. Zooarchaeology is widely interdisciplinary, global in scope, and practiced by a diverse, interconnected community of scholars with a wide range of experiences, theoretical interests, training, and methodologies.
This chapter is solely dedicated to reinforcement learning (RL), one of the three main learning paradigms covered in the book (together with regression and classification). The goal of RL is for an agent to learn from and respond to its environment modeled as a Markov decision process (MDP), by following a set of policies to take the best action at each state of the MDP, in order to receive the maximum total accumulated reward. The utmost goal is to come up with the optimal policy in terms of the best action to take at each state. Different from all optimization problems previously considered for maximizing (or minimizing) certain objective functions, RL achieves its goal by the general method of dynamic programming (while linear and quadratic programmings are for constrained optimization), which solves a complex problem by breaking it up and solving a set of subproblems recursively. Specifically, the main method for RL is the Q-learning algorithm which finds the optimal policy that takes the best action selected based on the expected values of the total reward at all states and all actions at each state. Toward to end of the chapter, various more advanced versions of RL are briefly discussed based on some previously learned methods such as neural networks and deep learning.
The practice of zooarchaeology requires familiarity with the types of animals represented in archaeological assemblages, particularly with hard tissues most likely to be present in the archaeological record. This knowledge must be grounded in a basic understanding of taxonomy (both folk and systematic), evolution, anatomy, and morphology. Modern zooarchaeology also requires familiarity with highly technical analyses, such as archaeogenetics, stable isotopes, and trace elements.
The goal of this chapter is to prepare for the future discussion of various artificial neural network (ANN) learning algorithms by introducing some basic concepts in neural networks and some biologically inspired examples the Habbian and Hopfield networks to illustrate how an ANN based on some simple learning rule can achieve meaningful results, although they are not actually widely used in machine learning practice. Specifically, the behavior of the Hebbian learning network mimics the associative nature of brain, as a simple model of associative memory, and the Hopfield network further shows how a pattern can be stored and then recalled based on a noisy and imcomplete copy of itself, a function that is commenly demonstratedof the brain.
Confidently analyze, interpret and act on financial data with this practical introduction to the fundamentals of financial data science. Master the fundamentals with step-by-step introductions to core topics will equip you with a solid foundation for applying data science techniques to real-world complex financial problems. Extract meaningful insights as you learn how to use data to lead informed, data-driven decisions, with over 50 examples and case studies and hands-on Matlab and Python code. Explore cutting-edge techniques and tools in machine learning for financial data analysis, including deep learning and natural language processing. Accessible to readers without a specialized background in finance or machine learning, and including coverage of data representation and visualization, data models and estimation, principal component analysis, clustering methods, optimization tools, mean/variance portfolio optimization and financial networks, this is the ideal introduction for financial services professionals, and graduate students in finance and data science.
Students have an almost insurmountable task in understanding statistics in the psychological sciences and applying them to a research study. This textbook tackles this source of stress by guiding students through the research process, start to finish, from writing a proposal and performing the study, to analysing the results and creating a report and presentation. This truly practical textbook explains psychology research methods in a conversational style, with additional material of interest placed in focus boxes alongside, so that students don't lose their way through the steps. Every step is detailed visually with processes paralleled in both SPSS and R, allowing instructors and students to learn both statistical packages or to bridge from one to the other. Students perform hands-on statistical exercises using real data, and both qualitative and mixed-methods research are covered. They learn effective ways to present information visually, and about free tools to collect and analyse data.
Designed for graduate students, instructors, and seasoned researchers, this is an essential guide for robust research design and methodology in applied linguistics, covering qualitative, quantitative, and mixed methods research. It adopts a structured approach, starting with the foundational principles of research design, methodology, and data collection and analysis, to writing and interpreting, explaining, and reporting research results, bringing together all the steps and processes of research from start to finish in one single volume in a way that is practical, easy to follow, and easy to understand. Throughout, the emphasis is on the process of research and the application of various research techniques and principles across different areas. These characteristics, coupled with numerous pedagogical features such as key term reviews, visuals, research scenarios, and many discussion and activity questions, make the book an indispensable reference and a valuable textbook for courses in second language and applied linguistics research.
Build a firm foundation for studying statistical modelling, data science, and machine learning with this practical introduction to statistics, written with chemical engineers in mind. It introduces a data–model–decision approach to applying statistical methods to real-world chemical engineering challenges, establishes links between statistics, probability, linear algebra, calculus, and optimization, and covers classical and modern topics such as uncertainty quantification, risk modelling, and decision-making under uncertainty. Over 100 worked examples using Matlab and Python demonstrate how to apply theory to practice, with over 70 end-of-chapter problems to reinforce student learning, and key topics are introduced using a modular structure, which supports learning at a range of paces and levels. Requiring only a basic understanding of calculus and linear algebra, this textbook is the ideal introduction for undergraduate students in chemical engineering, and a valuable preparatory text for advanced courses in data science and machine learning with chemical engineering applications.
Play has a significant role in children's learning and development. Play in the Early Years examines the central questions about play from the perspectives of children, families and educators, providing a comprehensive introduction to the theory and practice of play for children from birth to eight years. In its fourth edition, Play in the Early Years has been thoroughly updated in line with the revised Early Years Learning Framework and the new version of the Australian Curriculum. It takes both a both a theoretical and a practical approach, and covers recent research into conceptual play and wellbeing. The text looks at social, cultural and institutional approaches to play, and explores a range of strategies for successfully integrating play into early years settings and primary classrooms. Each chapter features case studies and play examples, with questions and reflection activities incorporated throughout to enhance learners' understanding.
Through reading this chapter, you will gain insights into Vygotsky’s cultural-historical conception of play and the range of contemporary models of play that have been informed by cultural-historical theory.
What is play? How does play develop? What is the relationship between play, learning and development? This book looks at these central questions from the perspectives of children, families, educators and what is known from research. You are encouraged to read and reflect on the content as you progress through the book. Although each chapter brings in different dimensions, the approach taken is interactive, with most chapters (but not all) inviting you to consider specific research into play practices, and to generate your own ideas/data to discuss or critique. We begin the journey in this first chapter by looking at your ideas and the writings of others on the topic ‘What is play?’
Chapter 4 presents textual features, text types and genres in the detail necessary for elucidating translation practice. Starting with texture as the essential distinction between a sequence of sentences and a text, it examines textual features, that is, those elements that serve to distinguish between texts and non-texts and that give texts their identity. Among the textual features discussed are cohesion and coherence, markers of cohesion and coherence, information structure and information flow (from old to new), and topic and thematic development (along with topic maintenance and the tracing of participants in discourse). Textual functions (text types) and genres are also discussed. The implications for translation of textual features, textual functions and genres are presented throughout the chapter with numerous examples. Armed with these basic concepts, readers are offered tips on textual and parallel text analysis and on how assistive texts (background texts, parallel texts) and online corpus tools can be used for translation tasks.
As advocates for play, teachers need to have a clear definition of play, a model of play used to guide their practice and a theory of play that underpins their philosophy of teaching and learning. This chapter brings together insights gained about play from all the chapters in this book and invites you to take a position on your own philosophy of play. We then ask you to become an advocate for children’s play.
Chapter 6 aims to help readers understand how variation and change affect language, so that translation practices and decisions are not based on personal biases and lay views about language but, rather, on a principled understanding of how language interacts with society. Another goal is to create awareness of the impact of social and use-related (contextual) factors on language so that translated texts respond to the requirements of the translation instructions. Other sociolinguistic notions reviewed in this chapter, along with their implications for translation are register, dialectal variation, socioeconomic variation, the nature of language change and variation, prestigious varieties vs. stigmatized varieties, and translating in multilingual societies. The discussion of register includes field of activity, medium and level of formality, as well as the implications for translation of not considering these within the context of the translation brief and translation norms. The connection between register selection and linguistic and translation competence is explained. Illustrative examples are used throughout the chapter.
In this chapter, we seek to examine how play supports children’s overall development. We specifically take the child’s perspective in planning for play development.This chapter has been designed to provide a strong theoretical sense of the concepts of play, learning and development in early education; the capacity to analyse and support play development; a look at planning for play and learning outcomes, drawing on the The Early Years Learning Framework for Australia (V2.0) or Te Whāriki.