Description : "Cutting Edge" is a series in English as a foreign language. It provides an all-round practical knowledge of grammar, skills, vocabulary and real-life functional language.
Description : This book presents the most modern and innovative techniques in ocular surgery currently utilized by experts in the field. All aspects of ocular surgery from the front to the back of the eye are covered in this resource, with all surgeries demonstrated as ‘recipes’ with first the ingredients and then the surgical techniques with step-by-step instructions. The surgeries are illustrated with photographs, drawings and videos for practical application, and the step-by-step presentation allows for quick and easy access to the most appropriate techniques in ocular surgery.
Description : In this book, leading experts discuss innovative components of complexity theory and chaos theory in economics. The underlying perspective is that investigations of economic phenomena should view these phenomena not as deterministic, predictable and mechanistic but rather as process dependent, organic and always evolving. The aim is to highlight the exciting potential of this approach in economics and its ability to overcome the limitations of past research and offer important new insights. The book offers a stimulating mix of theory, examples and policy. By casting light on a variety of topics in the field, it will provide an ideal platform for researchers wishing to deepen their understanding and identify areas for further investigation.
Description : Are you tired of the same old stuff (S.O.S.)? Do you long for something fresh and exciting? Then perhaps this book is for you. It takes a no-nonsense look at what is really happening. It addresses the issues you and I are facing right now.
Description : Using various research methodologies, such as reviews, case studies, analytical modeling and empirical studies, this book investigates luxury fashion retail management and provides relevant insights, which are beneficial to both industrialists and academics. Readers gain an understanding of luxury fashion retailing, including proper operations and strategic management, which now are the most crucial items on the luxury fashion industry’s senior management agenda.
Description : An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.
Description : As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
Description : Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
Description : Russian: From Intermediate to Advanced is a vibrant and modern course designed to help students achieve advanced proficiency in Russian. Offering a flexible modular approach structured around contemporary themes, the course further develops reading, listening, speaking, and writing skills while also expanding the student’s cultural literacy. Key features include: Structured chapters presenting a wide assortment of readings that include blogs, forums and surveys as well as opinion pieces and commentaries. Each text is accompanied by assignments with increasing levels of difficulty. Authentic and up-to-date readings, video and audio excerpts covering a range of relevant social and cultural topics, including Demography, Youth Culture, Politics and Society, Economics and Globalization. Video clips from news programs that are used not only to develop listening comprehension but also introduce students to contemporary Russian society. Particular attention to helping students acquire advanced vocabulary and the ability to converse, discuss and argue about issues with extended paragraph-length discourse. Special focus on the development of strong listening and reading comprehension skills, ensuring that students understand the ideas and supporting details in narrative and descriptive texts and connected discourse. A free companion website at http://www.russian.ucla.edu/AdvancedRussian/ offering student and instructor video and audio resources, sample syllabi and tests as well as additional materials. Written by a highly experienced author team that has co-authored the first year Russian textbook Beginner’s Russian (2010) and the second-year textbook V Puti (2005). Russian: From Intermediate to Advanced will be an essential resource for undergraduate students in their third and fourth year of Russian language study. It is also suitable for heritage learners of Russian who have mastered literacy and are familiar with the grammatical structure of Russian.
Description : Master practical strategic marketing analysis through real-life case studies and hands-on examples. In Cutting Edge Marketing Analytics, three pioneering experts integrate all three core areas of marketing analytics: statistical analysis, experiments, and managerial intuition. They fully detail a best-practice marketing analytics methodology, augmenting it with case studies that illustrate the quantitative and data analysis tools you'll need to allocate resources, define optimal marketing mixes; perform effective analysis of customers and digital marketing campaigns, and create high-value dashboards and metrics. For each marketing problem, the authors help you: Identify the right data and analytics techniques Conduct the analysis and obtain insights from it Outline what-if scenarios and define optimal solutions Connect your insights to strategic decision-making Each chapter contains technical notes, statistical knowledge, case studies, and real data you can use to perform the analysis yourself. As you proceed, you'll gain an in-depth understanding of: The real value of marketing analytics How to integrate quantitative analysis with managerial sensibility How to apply linear regression, logistic regression, cluster analysis, and Anova models The crucial role of careful experimental design For all marketing professionals specializing in marketing analytics and/or business intelligence; and for students and faculty in all graduate-level business courses covering Marketing Analytics, Marketing Effectiveness, or Marketing Metrics