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Machine Learning and Metaheuristics Algorithms, and Applications: First Symposium, SoMMA 2019, Trivandrum, India, December 18–21, 2019, Revised Selected Papers (Communications in Computer and Information Science #1203)
by Kuan-Ching Li Swagatam Das Sabu M. Thampi Michal Wozniak Stefano Berretti Ljiljana TrajkovicThis book constitutes the refereed proceedings of the First Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, held in Trivandrum, India, in December 2019.The 17 full papers and 6 short papers presented in this volume were thoroughly reviewed and selected from 53 qualified submissions. The papers cover such topics as machine learning, artificial intelligence, Internet of Things, modeling and simulation, disctibuted computing methodologies, computer graphics, etc.
Machine Learning and Metaheuristics Algorithms, and Applications: Second Symposium, SoMMA 2020, Chennai, India, October 14–17, 2020, Revised Selected Papers (Communications in Computer and Information Science #1366)
by Selwyn Piramuthu Kuan-Ching Li Sabu M. Thampi Michal Wozniak Stefano Berretti Dhananjay SinghThis book constitutes the refereed proceedings of the Second Symposium on Machine Learning and Metaheuristics Algorithms, and Applications, SoMMA 2020, held in Chennai, India, in October 2020. Due to the COVID-19 pandemic the conference was held online. The 12 full papers and 7 short papers presented in this volume were thoroughly reviewed and selected from 40 qualified submissions. The papers cover such topics as machine learning, artificial intelligence, Internet of Things, modeling and simulation, disctibuted computing methodologies, computer graphics, etc.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2021, Virtual Event, September 13-17, 2021, Proceedings, Part I (Communications in Computer and Information Science #1524)
by Christopher Buckley Min Zhou Lee Cooper Rita Ribeiro Donato Malerba Bodo Rosenhahn João Gama Riccardo Guidotti Anna Monreale Pedro M. Ferreira Meng Sun Philippe Fournier-Viger Ricard Gavaldà Michael Kamp Yamuna Krishnamurthy Valerio Bitetta Ilaria Bordino Andrea Ferretti Francesco Gullo Christine Largeron Massimiliano Ruocco Giovanni Ponti Tim Verbelen Pablo Lanillos Holger Fröning Franz Pernkopf Gregor Schiele Michaela Blott Lorenzo Severini Przemyslaw Biecek Irena Koprinska Linara Adilova Ibéria Medeiros Eirini Ntoutsi Salvatore Rinzivillo Jefrey Lijffijt Adrien Bibal Tassadit Bouadi Benoît Frénay Luis Galárraga José Oramas Bo Kang Tiphaine Viard Pascal Welke Erlend Aune Claudio Gallicchio Günther Schindler Mykola Pechenizkiy Daniela Cialfi Maxwell Ramstead Giuseppina Andresini M. Saqib Nawaz Sebastian Ventura Naghmeh Ghazaleh Jonas Richiardi Damian Roqueiro Diego Saldana Miranda Konstantinos Sechidis Guilherme GraçaThis two-volume set constitutes the refereed proceedings of the workshops which complemented the 21th Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD, held in September 2021. Due to the COVID-19 pandemic the conference and workshops were held online. The 104 papers were thoroughly reviewed and selected from 180 papers submited for the workshops. This two-volume set includes the proceedings of the following workshops:Workshop on Advances in Interpretable Machine Learning and Artificial Intelligence (AIMLAI 2021)Workshop on Parallel, Distributed and Federated Learning (PDFL 2021)Workshop on Graph Embedding and Mining (GEM 2021)Workshop on Machine Learning for Irregular Time-series (ML4ITS 2021)Workshop on IoT, Edge, and Mobile for Embedded Machine Learning (ITEM 2021)Workshop on eXplainable Knowledge Discovery in Data Mining (XKDD 2021)Workshop on Bias and Fairness in AI (BIAS 2021)Workshop on Workshop on Active Inference (IWAI 2021)Workshop on Machine Learning for Cybersecurity (MLCS 2021)Workshop on Machine Learning in Software Engineering (MLiSE 2021)Workshop on MIning Data for financial applications (MIDAS 2021)Sixth Workshop on Data Science for Social Good (SoGood 2021)Workshop on Machine Learning for Pharma and Healthcare Applications (PharML 2021)Second Workshop on Evaluation and Experimental Design in Data Mining and Machine Learning (EDML 2020)Workshop on Machine Learning for Buildings Energy Management (MLBEM 2021)
Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers, Part I (Communications in Computer and Information Science #2133)
by Fabrizio Silvestri Rosa MeoThe five-volume set CCIS 2133-2137 constitutes the refereed proceedings of the workshops held in conjunction with the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, during September 18-22, 2023. The 200 full papers presented in these proceedings were carefully reviewed and selected from 515 submissions. The papers have been organized in the following tracks: Part I: Advances in Interpretable Machine Learning and Artificial Intelligence -- Joint Workshop and Tutorial; BIAS 2023 - 3rd Workshop on Bias and Fairness in AI; Biased Data in Conversational Agents; Explainable Artificial Intelligence: From Static to Dynamic; ML, Law and Society; Part II: RKDE 2023: 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education; SoGood 2023 – 8th Workshop on Data Science for Social Good; Towards Hybrid Human-Machine Learning and Decision Making (HLDM); Uncertainty meets explainability in machine learning; Workshop: Deep Learning and Multimedia Forensics. Combating fake media and misinformation; Part III: XAI-TS: Explainable AI for Time Series: Advances and Applications; XKDD 2023: 5th International Workshop on eXplainable Knowledge Discovery in Data Mining; Deep Learning for Sustainable Precision Agriculture; Knowledge Guided Machine Learning; MACLEAN: MAChine Learning for EArth ObservatioN; MLG: Mining and Learning with Graphs; Neuro Explicit AI and Expert Informed ML for Engineering and Physical Sciences; New Frontiers in Mining Complex Patterns; Part IV: PharML, Machine Learning for Pharma and Healthcare Applications; Simplification, Compression, Efficiency and Frugality for Artificial intelligence; Workshop on Uplift Modeling and Causal Machine Learning for Operational Decision Making; 6th Workshop on AI in Aging, Rehabilitation and Intelligent Assisted Living (ARIAL); Adapting to Change: Reliable Multimodal Learning Across Domains; AI4M: AI for Manufacturing; Part V: Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications; Deep learning meets Neuromorphic Hardware; Discovery challenge; ITEM: IoT, Edge, and Mobile for Embedded Machine Learning; LIMBO - LearnIng and Mining for BlOckchains; Machine Learning for Cybersecurity (MLCS 2023); MIDAS - The 8th Workshop on MIning DAta for financial applicationS; Workshop on Advancements in Federated Learning.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers, Part II (Communications in Computer and Information Science #2134)
by Fabrizio Silvestri Rosa MeoThe five-volume set CCIS 2133-2137 constitutes the refereed proceedings of the workshops held in conjunction with the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, during September 18-22, 2023. The 200 full papers presented in these proceedings were carefully reviewed and selected from 515 submissions. The papers have been organized in the following tracks: Part I: Advances in Interpretable Machine Learning and Artificial Intelligence -- Joint Workshop and Tutorial; BIAS 2023 - 3rd Workshop on Bias and Fairness in AI; Biased Data in Conversational Agents; Explainable Artificial Intelligence: From Static to Dynamic; ML, Law and Society; Part II: RKDE 2023: 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education; SoGood 2023 – 8th Workshop on Data Science for Social Good; Towards Hybrid Human-Machine Learning and Decision Making (HLDM); Uncertainty meets explainability in machine learning; Workshop: Deep Learning and Multimedia Forensics. Combating fake media and misinformation; Part III: XAI-TS: Explainable AI for Time Series: Advances and Applications; XKDD 2023: 5th International Workshop on eXplainable Knowledge Discovery in Data Mining; Deep Learning for Sustainable Precision Agriculture; Knowledge Guided Machine Learning; MACLEAN: MAChine Learning for EArth ObservatioN; MLG: Mining and Learning with Graphs; Neuro Explicit AI and Expert Informed ML for Engineering and Physical Sciences; New Frontiers in Mining Complex Patterns; Part IV: PharML, Machine Learning for Pharma and Healthcare Applications; Simplification, Compression, Efficiency and Frugality for Artificial intelligence; Workshop on Uplift Modeling and Causal Machine Learning for Operational Decision Making; 6th Workshop on AI in Aging, Rehabilitation and Intelligent Assisted Living (ARIAL); Adapting to Change: Reliable Multimodal Learning Across Domains; AI4M: AI for Manufacturing; Part V: Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications; Deep learning meets Neuromorphic Hardware; Discovery challenge; ITEM: IoT, Edge, and Mobile for Embedded Machine Learning; LIMBO - LearnIng and Mining for BlOckchains; Machine Learning for Cybersecurity (MLCS 2023); MIDAS - The 8th Workshop on MIning DAta for financial applicationS; Workshop on Advancements in Federated Learning.
Machine Learning and Principles and Practice of Knowledge Discovery in Databases: International Workshops of ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Revised Selected Papers, Part V (Communications in Computer and Information Science #2137)
by Fabrizio Silvestri Rosa MeoThe five-volume set CCIS 2133-2137 constitutes the refereed proceedings of the workshops held in conjunction with the Joint European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2023, which took place in Turin, Italy, during September 18-22, 2023. The 200 full papers presented in these proceedings were carefully reviewed and selected from 515 submissions. The papers have been organized in the following tracks: Part I: Advances in Interpretable Machine Learning and Artificial Intelligence -- Joint Workshop and Tutorial; BIAS 2023 - 3rd Workshop on Bias and Fairness in AI; Biased Data in Conversational Agents; Explainable Artificial Intelligence: From Static to Dynamic; ML, Law and Society; Part II: RKDE 2023: 1st International Tutorial and Workshop on Responsible Knowledge Discovery in Education; SoGood 2023 – 8th Workshop on Data Science for Social Good; Towards Hybrid Human-Machine Learning and Decision Making (HLDM); Uncertainty meets explainability in machine learning; Workshop: Deep Learning and Multimedia Forensics. Combating fake media and misinformation; Part III: XAI-TS: Explainable AI for Time Series: Advances and Applications; XKDD 2023: 5th International Workshop on eXplainable Knowledge Discovery in Data Mining; Deep Learning for Sustainable Precision Agriculture; Knowledge Guided Machine Learning; MACLEAN: MAChine Learning for EArth ObservatioN; MLG: Mining and Learning with Graphs; Neuro Explicit AI and Expert Informed ML for Engineering and Physical Sciences; New Frontiers in Mining Complex Patterns; Part IV: PharML, Machine Learning for Pharma and Healthcare Applications; Simplification, Compression, Efficiency and Frugality for Artificial intelligence; Workshop on Uplift Modeling and Causal Machine Learning for Operational Decision Making; 6th Workshop on AI in Aging, Rehabilitation and Intelligent Assisted Living (ARIAL); Adapting to Change: Reliable Multimodal Learning Across Domains; AI4M: AI for Manufacturing; Part V: Challenges and Opportunities of Large Language Models in Real-World Machine Learning Applications; Deep learning meets Neuromorphic Hardware; Discovery challenge; ITEM: IoT, Edge, and Mobile for Embedded Machine Learning; LIMBO - LearnIng and Mining for BlOckchains; Machine Learning for Cybersecurity (MLCS 2023); MIDAS - The 8th Workshop on MIning DAta for financial applicationS; Workshop on Advancements in Federated Learning.
Machine Learning and the Internet of Things in Education: Models and Applications (Studies in Computational Intelligence #1115)
by John Bush Idoko Rahib AbiyevThis book is designed to provide rich research hub for researchers, teachers, and students to ease research hassle/challenges. The book is rich and comprehensive enough to provide answers to frequently asked research questions because the content of the book touches several disciplines cutting across computing, engineering, medicine, education, and sciences in general. The rich multidisciplinary contents of the book promise to leave all users satisfied. The valuable features in the book include but not limited to: demonstration of mathematical expressions for implementation of machine learning models, integration of learning techniques, and projection of future AI and IoT technologies. These technologies will enable systems to be simulative, predictive, and self-operating smart systems. The primary audience of the book include but not limited to researchers, teachers, and postgraduate and undergraduate students in computing, engineering, medicine, education, and science fields.
Machine Learning for Cyber Security: Third International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part I (Lecture Notes in Computer Science #12486)
by Xiangliang Zhang Xiaofeng Chen Hongyang Yan Qiben YanThis three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020.The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Cyber Security: Third International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part II (Lecture Notes in Computer Science #12487)
by Xiangliang Zhang Xiaofeng Chen Hongyang Yan Qiben YanThis three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020.The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Cyber Security: Third International Conference, ML4CS 2020, Guangzhou, China, October 8–10, 2020, Proceedings, Part III (Lecture Notes in Computer Science #12488)
by Xiangliang Zhang Xiaofeng Chen Hongyang Yan Qiben YanThis three volume book set constitutes the proceedings of the Third International Conference on Machine Learning for Cyber Security, ML4CS 2020, held in Xi’an, China in October 2020.The 118 full papers and 40 short papers presented were carefully reviewed and selected from 360 submissions. The papers offer a wide range of the following subjects: Machine learning, security, privacy-preserving, cyber security, Adversarial machine Learning, Malware detection and analysis, Data mining, and Artificial Intelligence.
Machine Learning for Medical Image Reconstruction: Second International Workshop, MLMIR 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings (Lecture Notes in Computer Science #11905)
by Daniel Rueckert Andreas Maier Florian Knoll Jong Chul YeThis book constitutes the refereed proceedings of the Second International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2019, held in conjunction with MICCAI 2019, in Shenzhen, China, in October 2019. The 24 full papers presented were carefully reviewed and selected from 32 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging; deep learning for computed tomography; and deep learning for general image reconstruction.
Machine Learning for Medical Image Reconstruction: Third International Workshop, MLMIR 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings (Lecture Notes in Computer Science #12450)
by Patricia Johnson Jong Chul Ye Farah Deeba Tobias WürflThis book constitutes the refereed proceedings of the Third International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2020, held in conjunction with MICCAI 2020, in Lima, Peru, in October 2020. The workshop was held virtually. The 15 papers presented were carefully reviewed and selected from 18 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.
Machine Learning in Educational Sciences: Approaches, Applications and Advances
by Myint Swe KhineThis comprehensive volume investigates the untapped potential of machine learning in educational settings. It examines the profound impact machine learning can have on reshaping educational research. Each chapter delves into specific applications and advancements, sheds light on theory-building, and multidisciplinary research, and identifies areas for further development. It encompasses various topics, such as machine-based learning in psychological assessment. It also highlights the power of machine learning in analyzing large-scale international assessment data and utilizing natural language processing for science education. With contributions from leading scholars in the field, this book provides a comprehensive, evidence-based framework for leveraging machine-learning approaches to enhance educational outcomes. The book offers valuable insights and recommendations that could help shape the future of educational sciences.
Machine Learning in Medicine
by Aeilko H. Zwinderman Ton J. CleophasMachine learning is a novel discipline concerned with the analysis of large and multiple variables data. It involves computationally intensive methods, like factor analysis, cluster analysis, and discriminant analysis. It is currently mainly the domain of computer scientists, and is already commonly used in social sciences, marketing research, operational research and applied sciences. It is virtually unused in clinical research. This is probably due to the traditional belief of clinicians in clinical trials where multiple variables are equally balanced by the randomization process and are not further taken into account. In contrast, modern computer data files often involve hundreds of variables like genes and other laboratory values, and computationally intensive methods are required. This book was written as a hand-hold presentation accessible to clinicians, and as a must-read publication for those new to the methods.
Machine Learning, Optimization, and Data Science: 6th International Conference, LOD 2020, Siena, Italy, July 19–23, 2020, Revised Selected Papers, Part II (Lecture Notes in Computer Science #12566)
by Panos Pardalos Giuseppe Nicosia Giovanni Giuffrida Renato Umeton Vincenzo Sciacca Varun Ojha Emanuele La Malfa Giorgio JansenThis two-volume set, LNCS 12565 and 12566, constitutes the refereed proceedings of the 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, held in Siena, Italy, in July 2020. The total of 116 full papers presented in this two-volume post-conference proceedings set was carefully reviewed and selected from 209 submissions. These research articles were written by leading scientists in the fields of machine learning, artificial intelligence, reinforcement learning, computational optimization, and data science presenting a substantial array of ideas, technologies, algorithms, methods, and applications.
Machine Learning: Architecture in the age of Artificial Intelligence
by Phil Bernstein‘The advent of machine learning-based AI systems demands that our industry does not just share toys, but builds a new sandbox in which to play with them.’ - Phil Bernstein The profession is changing. A new era is rapidly approaching when computers will not merely be instruments for data creation, manipulation and management, but, empowered by artificial intelligence, they will become agents of design themselves. Architects need a strategy for facing the opportunities and threats of these emergent capabilities or risk being left behind. Architecture’s best-known technologist, Phil Bernstein, provides that strategy. Divided into three key sections – Process, Relationships and Results – Machine Learning lays out an approach for anticipating, understanding and managing a world in which computers often augment, but may well also supplant, knowledge workers like architects. Armed with this insight, practices can take full advantage of the new technologies to future-proof their business. Features chapters on: Professionalism Tools and technologies Laws, policy and risk Delivery, means and methods Creating, consuming and curating data Value propositions and business models.
Machinist: Passbooks Study Guide (Career Examination Series #C-1414)
by National Learning CorporationThe Machinist Passbook® prepares you for your test by allowing you to take practice exams in the subjects you need to study. It provides hundreds of questions and answers in the areas that will likely be covered on your upcoming exam, including but not limited to: operation and maintenance of all machine shop equipment; hand tools and machine shop practices; machinery components; measuring devices and instruments; metals and heat treatment; reading comprehension and plan reading; related machine shop mathematics; safety; supervision and reports; and other related areas.
Macho Alfa
by Guido Galeano Vega Eunice T AndreLivro que trata de aspectos sociais e culturais de líderes em grupos animais e humanos. Macho Alfa Este conceito é mais bem aplicado no âmbito da natureza ou no sistema biológico animal. Nas sociedades modernas, é aplicado também para definir certo tipo de pessoas, que se caracterizam por sua capacidade de liderança. Como o conceito tem uma relação mais direta com o mundo animal, e mais ainda vinculado a certas espécies de predadores, implacáveis, de extrema eficiência no processo de caçada grupal, atividade motivada para garantir ou melhorar a possibilidade de sobrevivência em contextos de natureza selvagem, como é o caso dos lobos. Ele tem sido aplicado também nos grupos humanos com um estilo de vida de características similares.
Macmillan McGraw Hill Science
by Lucy H. DanielMacmillan/McGraw-Hill Science employs a unique lesson plan to develop science concepts three ways: through purposeful, hands-on activities; compelling reading content; and dynamic visuals and graphics. Key partnerships include Sally Ride Science and TIME For Kids.
Macro Photography Photo Workshop
by Haje Jan KampsSpecial techniques for creating unique, artistic, close-up images Macro, or close-up, photography is gaining popularity, and this book covers all of the challenges associated with taking great close-ups: depth of field, focus, and exposure. Copublished with Photoworkshop. com, a leading online educational resource for both beginning and professional photographers, this task-oriented reference allows readers to learn by doing and offers outstanding examples and instructions.
Macro Photography for Gardeners and Nature Lovers: The Essential Guide to Digital Techniques
by Alan L. DetrickGardeners and nature lovers delight in taking pictures—especially close-ups of flowers, butterflies, and insects. And though advances in digital camera technology have made taking, storing, and sharing photos easier than ever, taking top-quality pictures requires familiarity with both digital technology and the general principles of photography. Macro Photography for Gardeners and Nature Lovers provides exactly the information that aspiring photographers—no matter their level of skill—need to take their photos to the next level. Clear and concise chapters cover the basics of macro (close-up) photography, explain the features of current digital single-lens reflex cameras, show the many ways images can be composed, and share tips on digital effects, storage, and manipulation of imagery. Throughout the text, helpful tips, definitions, exercises, and case studies serve to demystify digital photography. Each lesson is supported by examples of the author's stunning photography. Whether taking photos of flowers and insects, compiling a photographic record of your garden, or simply sharing beautiful images with friends and family, everyone can become accomplished photographers of the world's small-scale wonders.
Macroanalysis: Digital Methods and Literary History
by Matthew L. JockersIn this volume, Matthew L. Jockers introduces readers to large-scale literary computing and the revolutionary potential of macroanalysis--a new approach to the study of the literary record designed for probing the digital-textual world as it exists today, in digital form and in large quantities. Using computational analysis to retrieve key words, phrases, and linguistic patterns across thousands of texts in digital libraries, researchers can draw conclusions based on quantifiable evidence regarding how literary trends are employed over time, across periods, within regions, or within demographic groups, as well as how cultural, historical, and societal linkages may bind individual authors, texts, and genres into an aggregate literary culture. Moving beyond the limitations of literary interpretation based on the "close-reading" of individual works, Jockers describes how this new method of studying large collections of digital material can help us to better understand and contextualize the individual works within those collections.
Macroeconomic Aspects of Aging and Retirement of College and University Teachers: Indo-French Perspectives
by Geeta NairThis book explores the universal and highly topical issues of ageing and retirement. It places a particular focus on the macroeconomic aspects of the ageing and retirement of college and university teachers, through a case study of teachers and professors in France and India. While the ageing of the population and the financing of the pension system are notoriously pressing issues in Western nations such as France, it has previously not been acknowledged that these issues are also critical to the development trajectory of emerging countries such as India. The book also highlights the importance of pensions for welfare, well-being and stability in all categories of workers, including workers in the informal sector and private companies devoid of pension schemes, where jobs are largely irregular and temporary in nature. It will be of great interest to researchers in the fields of comparative education, sociology and economics.
Macroeconomics, 23rd Edition
by Stanley L. Brue Sean M. Flynn Campbell R. McConnellMaximize your results effortlessly. Experience unparalleled outcomes with McConnell/Brue/Flynn – a streamlined solution for elevating your success. When presented with the choice to work harder or smarter, this product empowers you to choose the latter. Revolutionize your approach to economics education with a contemporary learning tool that simplifies both teaching and learning. Macroeconomics provides a cutting-edge experience for instructors and students, offering real-life examples and advanced digital resources. Dive into interactive, immersive, and adaptive learning assignments, creating a student-centric environment that transforms the way subjects are presented. For instructors, our comprehensive teaching package takes care of the heavy lifting, allowing you to concentrate on what you love.
Macroeconomics, 6th Custom Edition for Temple University
by Michael ParkinMacroeconomics seeks to put clarity and understanding in the grasp of the student with a careful and vivid exploration of the tension between self-interest and the social interest, the role and power of incentives--of opportunity cost and marginal benefit--and demonstrating the possibility that markets supplemented by other mechanisms might allocate resources efficiently. Parkin students begin to think about issues the way real economists do and learn how to explore difficult policy problems and make more informed decisions in their own economic lives.