Python data mining and machine learning in action

Over the last decade, cost pressures, technology, automation, globalisation, de-regulation, and changing client relationships have transformed the practice of law, but legal education has been slow to respond. Deciding what learning objectives a law degree ought to prioritise, and how to best strike the balance between vocational and academic training, are questions of growing importance for students, regulators, educators, and the legal profession. This collection provides a range of perspectives on the suite of skills required by the future lawyer and the various approaches to supporting their acquisition. Contributions report on a variety of curriculum initiatives, including role-play, gamification, virtual reality, project-based learning, design thinking, data analytics, clinical legal education, apprenticeships, experiential learning and regulatory reform, and in doing so, offer a vision of what modern legal education might look like.

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overv

This friendly guide is the companion you need to convert pure mathematics into understanding and facility with a host of probabilistic tools. The book provides a high-level view of probability and its most powerful applications. It begins with the basic rules of probability and quickly progresses to some of the most sophisticated modern techniques in use, including Kalman filters, Monte Carlo techniques, machine learning methods, Bayesian inference and stochastic processes. It draws on thirty years of experience in applying probabilistic methods to problems in computational science and engineering, and numerous practical examples illustrate where these techniques are used in the real world. Topics of discussion range from carbon dating to Wasserstein GANs, one of the most recent developments in Deep Learning. The underlying mathematics is presented in full, but clarity takes priority over complete rigour, making this text a starting reference source for researchers and a readable overv

Quilters want to finish their quilts--and that means doing their own machine quilting. In Free-Motion Quilting 101, teacher and quilter Ashley Nickels provides in-depth instruction on learning the tec

World War II played an important role in the trajectory of race and American political development, but the War's effects were much more complex than many assume. Steven White offers an extensive analysis of rarely utilized survey data and archival evidence to assess white racial attitudes and the executive branch response to civil rights advocacy. He finds that, contrary to conventional wisdom, the white mass public's racial policy attitudes largely did not liberalize during the war against Nazi Germany. In this context, advocates turned their attention to the possibility of unilateral action by the president, emphasizing a wartime civil rights agenda focused on discrimination in the defense industry and segregation in the military. This book offers a reinterpretation of this critical period in American political development, as well as implications for the theoretical relationship between war and the inclusion of marginalized groups in democratic societies.

The tenth edition of Operating System Concepts has been revised to keep it fresh and up-to-date with contemporary examples of how operating systems function, and to improve learning and the student's experience with the material. It combines instruction on concepts with real-world applications so that students can understand the practical usage of the content. End-of-chapter practice exercises help to further reinforce important concepts.Each chapter also includes homework exercises and additional suggested readings on core topics. The text provides several example programs written in C and Java for use in several programming environments and a Linux Virtual Machine that can be run on Windows 10, Linux, or macOS.

1. Added material on important techniques for data mining, including regression trees and neural network models in Chapters 11 and 13.2. The Chapter on logistic regression (Chapter 14) has been extens

A clear introduction to lexical-functional grammar (LFG), this outstanding textbook sets out a formal approach to the study of language using a step-by-step approach and rich language data. Data from English and a range of other languages is used to illustrate the main concepts, allowing those students not accustomed to working with cross-linguistic data to familiarize themselves with the theory, while also enabling those interested in how the theory can account for more challenging data sets to extend their learning. Exercises ranging from simple technical questions to analyses of a data set, as well as a further resources section with a literature review complete each chapter. The book aims to equip readers with the skills to analyze new data sets and to begin to engage with the primary LFG literature.

A clear introduction to lexical-functional grammar (LFG), this outstanding textbook sets out a formal approach to the study of language using a step-by-step approach and rich language data. Data from English and a range of other languages is used to illustrate the main concepts, allowing those students not accustomed to working with cross-linguistic data to familiarize themselves with the theory, while also enabling those interested in how the theory can account for more challenging data sets to extend their learning. Exercises ranging from simple technical questions to analyses of a data set, as well as a further resources section with a literature review complete each chapter. The book aims to equip readers with the skills to analyze new data sets and to begin to engage with the primary LFG literature.

Primary Mathematics: Integrating Theory with Practice provides a comprehensive introduction to teaching and learning mathematics in today's classrooms. Closely aligned with the Australian Curriculum: Mathematics, this text covers the core learning areas of measurement, space and geometry, early number concepts, data and statistics, chance and probability, and patterns and algebra. The text also addresses key considerations for teachers, such as planning, assessment, differentiation and teaching outside traditional contexts. The third edition has been thoroughly revised and features three new chapters focusing on the General Capabilities and Cross-Curricular Priorities, implementing STEM strategies in the primary setting, and the transition to practice. Each chapter highlights how the theory of teaching mathematics can be put into practice effectively and includes new guided reflective questions and student tasks. Written by an expert author team, Primary Mathematics remains an essentia

Explore aircraft carriers in this high-interest look at an exciting military machine. The history of aircraft carriers, their parts, and how they are used in action are covered with leveled text and v

This unique text provides a thorough, yet accessible, grounding in the mathematics, statistics, and programming that students need to master for coursework and research in climate science, meteorology, and oceanography. Assuming only high school mathematics, it presents carefully selected concepts and techniques in linear algebra, statistics, computing, calculus and differential equations within the context of real climate science examples. Computational techniques are integrated to demonstrate how to visualize, analyze, and apply climate data, with R code featured in the book and both R and Python code available online. Exercises are provided at the end of each chapter with selected solutions available to students to aid self-study and further solutions provided online for instructors only. Additional online supplements to aid classroom teaching include datasets, images, and animations. Guidance is provided on how the book can support a variety of courses at different levels, making i

Exploring the origins and evolution of magnetic fields in planets, stars and galaxies, this book gives a basic introduction to magnetohydrodynamics and surveys the observational data, with particular focus on geomagnetism and solar magnetism. Pioneering laboratory experiments that seek to replicate particular aspects of fluid dynamo action are also described. The authors provide a complete treatment of laminar dynamo theory, and of the mean-field electrodynamics that incorporates the effects of random waves and turbulence. Both dynamo theory and its counterpart, the theory of magnetic relaxation, are covered. Topological constraints associated with conservation of magnetic helicity are thoroughly explored and major challenges are addressed in areas such as fast-dynamo theory, accretion-disc dynamo theory and the theory of magnetostrophic turbulence. The book is aimed at graduate-level students in mathematics, physics, Earth sciences and astrophysics, and will be a valuable resource for

The fifth edition of The Cosmos: Astronomy in the New Millennium provides you with the fundamentals of astronomical knowledge that have been built up over decades, with an expanded discussion of the incredible advances that are now taking place in this fast-paced field, such as New Horizons' flyby of Pluto, exoplanets, 'dark matter', and the direct detection of gravitational waves by the Laser Interferometer Gravitational-Wave Observatory (LIGO). Written in a clear and easily understandable style, this textbook has been thoroughly revised to include updated data and figures, new images from recent space missions and telescopes, the latest discoveries on supernovae, and new observations of the region around the four-million-solar-mass black hole at the center of our Milky Way Galaxy. A rich array of teaching and learning resources is available at http://thecosmos5.com. The website is regularly updated to include the latest discoveries and photographs in the field.

A complete resource for finance students, this textbook presents the most common empirical approaches in finance in a comprehensive and well-illustrated manner that shows how econometrics is used in practice, and includes detailed case studies to explain how the techniques are used in relevant financial contexts. Maintaining the accessible prose and clear examples of previous editions, the new edition of this best-selling textbook provides support for the main industry-standard software packages, expands the coverage of introductory mathematical and statistical techniques into two chapters for students without prior econometrics knowledge, and includes a new chapter on advanced methods. Learning outcomes, key concepts and end-of-chapter review questions (with full solutions online) highlight the main chapter takeaways and allow students to self-assess their understanding. Online resources include extensive teacher and student support materials, including EViews, Stata, R, and Python so

Recent years have witnessed an explosion in the volume and variety of data collected in all scientific disciplines and industrial settings. Such massive data sets present a number of challenges to researchers in statistics and machine learning. This book provides a self-contained introduction to the area of high-dimensional statistics, aimed at the first-year graduate level. It includes chapters that are focused on core methodology and theory - including tail bounds, concentration inequalities, uniform laws and empirical process, and random matrices - as well as chapters devoted to in-depth exploration of particular model classes - including sparse linear models, matrix models with rank constraints, graphical models, and various types of non-parametric models. With hundreds of worked examples and exercises, this text is intended both for courses and for self-study by graduate students and researchers in statistics, machine learning, and related fields who must understand, apply, and ad

Exploring the origins and evolution of magnetic fields in planets, stars and galaxies, this book gives a basic introduction to magnetohydrodynamics and surveys the observational data, with particular focus on geomagnetism and solar magnetism. Pioneering laboratory experiments that seek to replicate particular aspects of fluid dynamo action are also described. The authors provide a complete treatment of laminar dynamo theory, and of the mean-field electrodynamics that incorporates the effects of random waves and turbulence. Both dynamo theory and its counterpart, the theory of magnetic relaxation, are covered. Topological constraints associated with conservation of magnetic helicity are thoroughly explored and major challenges are addressed in areas such as fast-dynamo theory, accretion-disc dynamo theory and the theory of magnetostrophic turbulence. The book is aimed at graduate-level students in mathematics, physics, Earth sciences and astrophysics, and will be a valuable resource for

In response to the escalating need for up-to-date information on writers, Contemporary Authors New Revision Series brings researchers the most recent data on the worlds most-popular authors. These e

A comprehensive introduction to how people learn second languages (L2s), this textbook approaches the topic through five problems the L2 learner has to solve: 'breaking into' the L2; associating forms with meanings; learning sentence structure; learning phrasal and sentential meaning; and learning the use of the L2 in context. These problems are linked throughout to the L2 acquisition of lexis, morphology, syntax, semantics, phonetics/phonology and language-use in a reader-friendly way, using key studies to build a comprehensive picture of how L2s are learned. 'In a nutshell' summaries of chapter sections provide helpful signposts to the developing argument, whilst end-of-chapter activities encourage the reader to reflect on the ideas presented, analyse data and think creatively about the problems encountered. The roles of innate knowledge, input, and the age at which learning starts are also considered. This essential textbook will enable students to think objectively about language,

A comprehensive introduction to how people learn second languages (L2s), this textbook approaches the topic through five problems the L2 learner has to solve: 'breaking into' the L2; associating forms with meanings; learning sentence structure; learning phrasal and sentential meaning; and learning the use of the L2 in context. These problems are linked throughout to the L2 acquisition of lexis, morphology, syntax, semantics, phonetics/phonology and language-use in a reader-friendly way, using key studies to build a comprehensive picture of how L2s are learned. 'In a nutshell' summaries of chapter sections provide helpful signposts to the developing argument, whilst end-of-chapter activities encourage the reader to reflect on the ideas presented, analyse data and think creatively about the problems encountered. The roles of innate knowledge, input, and the age at which learning starts are also considered. This essential textbook will enable students to think objectively about language,

This book highlights the quantitative methods of data mining and information visualization and explores their use in relation to the films and writings of the Russian director, Dziga Vertov. The theor

The skill of statistical thinking is increasing in importance in this predominantly data-driven world. With Mendenhall, Beaver and Beaver's INTRODUCTION TO PROBABILITY AND STATISTICS, 15th Edition,

●PRINCIPLES OF INSTRUMENTAL ANALYSIS offers the most current data in its coverage and end-of-chapter problem sets, and the authors present material in a student-friendly style that is active and engag

Integration of research experiences into the undergraduate classroom can result in increased recruitment, retention, and motivation of science students. 'Big data' science initiatives, such as the Paleobiology Database (PBDB), can provide inexpensive and accessible research opportunities. This Element provides an introduction to what the PBDB is, how to use it, how it can be deployed in introductory and advanced courses, and examples of how it has been used in undergraduate research. The PBDB aims to provide information on all fossil organisms, across the tree of life, around the world, and through all of geologic time. The PBDB Resource Page contains a range of PBDB tutorials and activities for use in physical geology, historical geology, paleontology, sedimentology, and stratigraphy courses. As two-year colleges, universities, and distance-based learning initiatives seek research-based alternatives to traditional lab exercises, the PBDB can provide opportunities for hands-on science

Stochastic differential equations are differential equations whose solutions are stochastic processes. They exhibit appealing mathematical properties that are useful in modeling uncertainties and noisy phenomena in many disciplines. This book is motivated by applications of stochastic differential equations in target tracking and medical technology and, in particular, their use in methodologies such as filtering, smoothing, parameter estimation, and machine learning. It builds an intuitive hands-on understanding of what stochastic differential equations are all about, but also covers the essentials of Itô calculus, the central theorems in the field, and such approximation schemes as stochastic Runge–Kutta. Greater emphasis is given to solution methods than to analysis of theoretical properties of the equations. The book's practical approach assumes only prior understanding of ordinary differential equations. The numerous worked examples and end-of-chapter exercises include application-

Stochastic differential equations are differential equations whose solutions are stochastic processes. They exhibit appealing mathematical properties that are useful in modeling uncertainties and noisy phenomena in many disciplines. This book is motivated by applications of stochastic differential equations in target tracking and medical technology and, in particular, their use in methodologies such as filtering, smoothing, parameter estimation, and machine learning. It builds an intuitive hands-on understanding of what stochastic differential equations are all about, but also covers the essentials of Itô calculus, the central theorems in the field, and such approximation schemes as stochastic Runge–Kutta. Greater emphasis is given to solution methods than to analysis of theoretical properties of the equations. The book's practical approach assumes only prior understanding of ordinary differential equations. The numerous worked examples and end-of-chapter exercises include application-

People hold a variety of prior conceptions that impact their learning. Prior conceptions that include erroneous or incomplete understandings represent a significant barrier to durable learning, as they are often difficult to change. While researchers have documented students' prior conceptions in many areas of geoscience, little is known about prior conceptions involving paleontology. In this Element, data on student prior conceptions from two introductory undergraduate paleontology courses are presented. In addition to more general misunderstandings about the nature of science, many students hold incorrect ideas about methods of historical geology, Earth history, ancient life, and evolution. Of special note are student perceptions of the limits of paleontology as scientific inquiry. By intentionally eliciting students' prior conceptions and implementing the pedagogical strategies described in other Elements in this series, lecturers can shape instruction to challenge this negative vie

Getting Ready to Learn describes how educational media have and are continuing to play a role in meeting the learning needs of children, parents, and teachers. Based on years of meaningful data from t

Getting Ready to Learn describes how educational media have and are continuing to play a role in meeting the learning needs of children, parents, and teachers. Based on years of meaningful data from t

Artificial intelligence and related technologies are changing both the law and the legal profession. In particular, technological advances in fields ranging from machine learning to more advanced robo

In response to the escalating need for up-to-date information on writers, Contemporary Authors New Revision Series brings researchers the most recent data on the worlds most-popular authors. These e

This book presents original, empirical data from quantitative and qualitative research studies in the field of language learning aptitude, ability, and individual differences. It does so from the pers

Geometric and topological inference deals with the retrieval of information about a geometric object using only a finite set of possibly noisy sample points. It has connections to manifold learning and provides the mathematical and algorithmic foundations of the rapidly evolving field of topological data analysis. Building on a rigorous treatment of simplicial complexes and distance functions, this self-contained book covers key aspects of the field, from data representation and combinatorial questions to manifold reconstruction and persistent homology. It can serve as a textbook for graduate students or researchers in mathematics, computer science and engineering interested in a geometric approach to data science.

A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences Optimization Techn

Recent startling successes in machine intelligence using a technique called ‘deep learning’ seem to blur the line between human and machine as never before. Are computers on the cusp of be

Recent startling successes in machine intelligence using a technique called ‘deep learning’ seem to blur the line between human and machine as never before. Are computers on the cusp of be

An essential guide to two burgeoning topics in machine learning – classification trees and ensemble learning Ensemble Classification Methods with Applications in R introduces the concepts a

This book shows machine learning enthusiasts and practitioners how to get the best of both worlds by deriving Fisher kernels from deep learning models. In addition, the book shares insight on how to s