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Author: International Monetary Fund Publisher: International Monetary Fund ISBN: 1451980167 Category : Business & Economics Languages : en Pages : 42
Book Description
This paper is concerned with debt-equity swaps in which foreign residents are a party to the exchange (i.e., it does not deal with flight capital), and with debt forgiveness. The seemingly unrelated issues of debt-equity swaps and debt forgiveness are jointly treated in this study, because debt forgiveness is in fact a special case of debt-equity swaps. Namely, it is a swap in which a positive amount of debt is exchanged for zero equity. For this reason these two problems have many common features.
Author: International Monetary Fund Publisher: International Monetary Fund ISBN: 1451980167 Category : Business & Economics Languages : en Pages : 42
Book Description
This paper is concerned with debt-equity swaps in which foreign residents are a party to the exchange (i.e., it does not deal with flight capital), and with debt forgiveness. The seemingly unrelated issues of debt-equity swaps and debt forgiveness are jointly treated in this study, because debt forgiveness is in fact a special case of debt-equity swaps. Namely, it is a swap in which a positive amount of debt is exchanged for zero equity. For this reason these two problems have many common features.
Author: Elhanan Helpman Publisher: ISBN: Category : Debt Languages : en Pages : 48
Book Description
Recent attempts to resolve the international debt crisis have lead some countries to engage in debt-equity swaps. The paper explores conditions under which such transactions are beneficial to the debtor as well as the creditors. It identifies a market failure that may prevent the emergence of actually beneficial swaps and analyzes the effects of swaps on the investment level in the debtor country. The latter helps to evaluate the contribution of this policy to future difficulties with debt service payments.
Author: Vikas (Vik) Kumar Publisher: Packt Publishing Ltd ISBN: 1787283224 Category : Computers Languages : en Pages : 258
Book Description
Add a touch of data analytics to your healthcare systems and get insightful outcomes Key Features Perform healthcare analytics with Python and SQL Build predictive models on real healthcare data with pandas and scikit-learn Use analytics to improve healthcare performance Book Description In recent years, machine learning technologies and analytics have been widely utilized across the healthcare sector. Healthcare Analytics Made Simple bridges the gap between practising doctors and data scientists. It equips the data scientists’ work with healthcare data and allows them to gain better insight from this data in order to improve healthcare outcomes. This book is a complete overview of machine learning for healthcare analytics, briefly describing the current healthcare landscape, machine learning algorithms, and Python and SQL programming languages. The step-by-step instructions teach you how to obtain real healthcare data and perform descriptive, predictive, and prescriptive analytics using popular Python packages such as pandas and scikit-learn. The latest research results in disease detection and healthcare image analysis are reviewed. By the end of this book, you will understand how to use Python for healthcare data analysis, how to import, collect, clean, and refine data from electronic health record (EHR) surveys, and how to make predictive models with this data through real-world algorithms and code examples. What you will learn Gain valuable insight into healthcare incentives, finances, and legislation Discover the connection between machine learning and healthcare processes Use SQL and Python to analyze data Measure healthcare quality and provider performance Identify features and attributes to build successful healthcare models Build predictive models using real-world healthcare data Become an expert in predictive modeling with structured clinical data See what lies ahead for healthcare analytics Who this book is for Healthcare Analytics Made Simple is for you if you are a developer who has a working knowledge of Python or a related programming language, although you are new to healthcare or predictive modeling with healthcare data. Clinicians interested in analytics and healthcare computing will also benefit from this book. This book can also serve as a textbook for students enrolled in an introductory course on machine learning for healthcare.
Author: Brian J. Evans Publisher: CRC Press ISBN: 1000449297 Category : Computers Languages : en Pages : 323
Book Description
Everyday technology is constantly changing, and it’s hard to keep up with it at times. What is all this talk about automation, STEM, analytics and super-computers, and how will it really affect my daily life at work and in the home? This book is a simple guide to everyday technology and analytics written in plain language. It starts with explaining how computer networks are increasing in speed so fast that we can do more in less time than ever before. It explains the analytical jargon in plain English and why robotics in the home will be aided by the new technology of the quantum computer. Richly furnished with over 200 illustrations, photos and with minimal equations, A Simple Guide to Technology and Analytics is a ready reference book for those times when you don’t really understand the technology and analytics being talked about. It explains complicated topics such as automated character recognition in a very simple way, and has simple exercises for the reader to fully understand the technology (with answers at the back). It even has explanations on how home appliances work, which are very useful the next time you go shopping for a microwave or TV. Even the Glossary at the back can be used as a quick look-up explanation for those on the go.
Author: Curtis Seare Publisher: Independently Published ISBN: 9781795224734 Category : Computers Languages : en Pages : 90
Book Description
This book will give you the critical information you need to create, use, and validate simple predictive models, and it will suggest the types of real-world business problems you can solve with those models. It is designed to be as simple as possible, providing basic, practical, and immediately applicable information for business users new to the world of predictive modeling. In summary: An introduction to and some fundamentals for good analysis A process outline to make analysis quick and effective A description of some of the most used predictive models and methods, and how they relate to business questions Comprehensive "How To" sections, including step-by-step Excel tutorials and common pitfalls to avoid Our approach is as follows: First, introduce analysis fundamentals. These are the basics of doing good and accurate analysis, and it will be important to keep these principles in mind as you create predictive models. Second, explain the process that will allow you to follow some easy, predefined steps to creating your own predictive models. This is a "big-picture" process flow meant to give you a basic procedure to follow no matter what type of predictive model you need to create. Last, this guide gives you an in-depth look into various predictive modeling techniques, organized according to the type of data you have and the type of questions you're trying to answer. This section makes up the bulk of the book, and the explanation of each model tells you what the predictive model looks like, what it can be used for, the assumptions necessary to use the model, a process to follow to create it (including step-by-step instructions in Excel), an explanation of some common errors to watch for, and a section on analyzing your results. The modeling process you will learn is as follows: 1. Choose a predictive model according to the business question. 2. Check to see if all the conditions for the model are met. 3. Carry out the analysis. 4. Check for statistical significance and fit. 5. Validate the predictive model. 6. Refine the predictive model. The basic models we go over in this text: General Regression (linear, multivariate, exponential, logarithmic, polynomial, time series) Logistic Regression ANOVA (t-test, one and two-way ANOVA) Chi-Square These models cover four common prediction cases you will encounter: Predict a numerical outcome with numerical explanatory variables Predict a yes or no outcome with numerical explanatory variables Predict a numerical outcome with categorical explanatory variables Predict a categorical outcome with categorical explanatory variables What you will not get in this book: Complex statistical explanations Complex math Complex predictive models (read: machine learning is not covered) Python, R, or other coding languages used for modeling What you will get in this book: Simple statistics Simple math Simple predictive models Modeling procedures using Excel Suggestions on how to apply these to real business situations Also, this book may or may not mention wombats.
Author: Jerri L. Ledford Publisher: John Wiley and Sons ISBN: 1118081595 Category : Computers Languages : en Pages : 432
Book Description
Get the most out of the free Google Analytics service—and get more customers Google Analytics allows you to discover vital information about how end users interact with their Web sites by collecting vital data and providing tools to analyze it, with the intention of improving the end-user experience and, ultimately converting users into customers. This indispensible guide delves into the latest updates to the newest version of Google Analytics—3.0—and explains the concepts behind this amazing free tool. You'll discover what information to track, how to choose the right goals and filters, techniques for reading Google Analytics reports and graphs, and, most importantly, how to compile this data and use it to improve your Web site and attract more potential customers. Takes an in-depth look at Google Analytics 3.0 and walks you through the possibilities it offers Explains how to read Google Analytics reports and graphs so that you can compile this data and use it to improve your Web site and attract more users Shares techniques for converting end users into customers Features tips and suggestions for getting the information you need from Google Analytics reports and then converting that information into actionable tasks you can use With Google Analytics, Third Edition, you&'ll be well on your way to retrieving the information you need to convert visitors to your site into customers! Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.
Author: Raghunath Nambiar Publisher: Springer ISBN: 3319153501 Category : Computers Languages : en Pages : 218
Book Description
This book constitutes the refereed post-conference proceedings of the 6th TPC Technology Conference, TPCTC 2014, held in Hangzhou, China, in September 2014. It contains 12 selected peer-reviewed papers, a report from the TPC Public Relations Committee. Many buyers use TPC benchmark results as points of comparison when purchasing new computing systems. The information technology landscape is evolving at a rapid pace, challenging industry experts and researchers to develop innovative techniques for evaluation, measurement and characterization of complex systems. The TPC remains committed to developing new benchmark standards to keep pace and one vehicle for achieving this objective is the sponsorship of the Technology Conference on Performance Evaluation and Benchmarking (TPCTC). Over the last five years TPCTC has been held successfully in conjunction with VLDB.
Author: Karl Michael Popp Publisher: BoD – Books on Demand ISBN: 3758301866 Category : Business & Economics Languages : en Pages : 202
Book Description
This book addresses key issues during the creation of corporate strategy and M&A strategy by explaining how to define a complete and consistent strategy, use an all-encompassing scope for the strategy to avoid blind spots, include ecosystem and platform strategy, define M&A strategy and its exact relationships to corporate strategy, and how to define strategic fit of two companies. It also lays the foundation for a data-driven strategy.
Author: International Monetary Fund
Author: International Monetary Fund
Author: Stephen Few
Author: Pradeep Srivastava
Author: Elhanan Helpman
Author: Vikas (Vik) Kumar
Author: Brian J. Evans
Author: Curtis Seare
Author: Jerri L. Ledford
Author: Raghunath Nambiar
Author: Karl Michael Popp