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Author: United Nations. Statistical Commission
Publisher:
Published: 1994
Total Pages: 256
ISBN-13:
DOWNLOAD EBOOKThe first volume defined statistical data editing and presented associated methods and software. This volume, containing some 30 contributions divided into six chapters, addresses how to solve individual data editing tasks, focusing on efficient techniques for data editing operations and for evaluat
Author: Sebastian Raschka
Publisher: Packt Publishing Ltd
Published: 2015-09-23
Total Pages: 455
ISBN-13: 1783555149
DOWNLOAD EBOOKUnlock 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.
Author: Lynne Billard
Publisher: John Wiley & Sons
Published: 2012-05-14
Total Pages: 330
ISBN-13: 0470090170
DOWNLOAD EBOOKWith the advent of computers, very large datasets have become routine. Standard statistical methods don’t have the power or flexibility to analyse these efficiently, and extract the required knowledge. An alternative approach is to summarize a large dataset in such a way that the resulting summary dataset is of a manageable size and yet retains as much of the knowledge in the original dataset as possible. One consequence of this is that the data may no longer be formatted as single values, but be represented by lists, intervals, distributions, etc. The summarized data have their own internal structure, which must be taken into account in any analysis. This text presents a unified account of symbolic data, how they arise, and how they are structured. The reader is introduced to symbolic analytic methods described in the consistent statistical framework required to carry out such a summary and subsequent analysis. Presents a detailed overview of the methods and applications of symbolic data analysis. Includes numerous real examples, taken from a variety of application areas, ranging from health and social sciences, to economics and computing. Features exercises at the end of each chapter, enabling the reader to develop their understanding of the theory. Provides a supplementary website featuring links to download the SODAS software developed exclusively for symbolic data analysis, data sets, and further material. Primarily aimed at statisticians and data analysts, Symbolic Data Analysis is also ideal for scientists working on problems involving large volumes of data from a range of disciplines, including computer science, health and the social sciences. There is also much of use to graduate students of statistical data analysis courses.
Author: Yves Balasko
Publisher: MIT Press
Published: 2009-04-17
Total Pages: 245
ISBN-13: 0262262045
DOWNLOAD EBOOKA leading scholar in the field presents post-1970s developments in the theory of general equilibrium, unified by the concept of equilibrium manifold. In The Equilibrium Manifold, noted economic scholar and major contributor to the theory of general equilibrium Yves Balasko argues that, contrary to what many textbooks want readers to believe, the study of the general equilibrium model did not end with the existence and welfare theorems of the 1950s. These developments, which characterize the modern phase of the theory of general equilibrium, led to what Balasko calls the postmodern phase, marked by the reintroduction of differentiability assumptions and the application of the methods of differential topology to the study of the equilibrium equation. Balasko's rigorous study demonstrates the central role played by the equilibrium manifold in understanding the properties of the Arrow-Debreu model and its extensions. Balasko argues that the tools of differential topology articulated around the concept of equilibrium manifold offer powerful methods for studying economically important issues, from existence and uniqueness to business cycles and economic fluctuations. After an examination of the theory of general equilibrium's evolution in the hundred years between Walras and Arrow-Debreu, Balasko discusses the properties of the equilibrium manifold and the natural projection. He highlights the important role of the set of no-trade equilibria, the structure of which is applied to the global structure of the equilibrium manifold. He also develops a geometric approach to the study of the equilibrium manifold. Applications include stability issues of adjustment dynamics for out-of-equilibrium prices, the introduction of price-dependent preferences, and aspects of time and uncertainty in extensions of the general equilibrium model that account for various forms of market frictions and imperfections. Special effort has been made at reducing the mathematical technicalities without compromising rigor. The Equilibrium Manifold makes clear the ways in which the postmodern” developments of the Arrow-Debreu model improve our understanding of modern market economies.
Author: José Antonio Ocampo
Publisher: Oxford Handbooks
Published: 2014-08-11
Total Pages: 0
ISBN-13: 9780198716136
DOWNLOAD EBOOKLatin America has been central to the main debates on development economics, ranging from the relationships between income inequality and economic growth, and the importance of geography versus institutions in development, to debates on the effects of trade, trade openness and protection on growth and income distribution. Despite increasing interest in the region there are few English language books on Latin American economics. This Handbook, organized into five parts, aims to fill this significant gap. Part I looks at long-term issues, including the institutional roots of Latin America's underdevelopment, the political economy of policy making, the rise, decline and re-emergence of alternative paradigms, and the environmental sustainability of the development pattern. Part II considers macroeconomic topics, including the management of capital account booms and busts, the evolution and performance of exchange rate regimes, the advances and challenges of monetary policies and financial development, and the major fiscal policy issues confronting the region, including a comparison of Latin American fiscal accounts with those of the OECD. Part III analyzes the region's economies in global context, particularly the role of Latin America in the world trade system and the effects of dependence on natural resources (characteristic of many countries of the region) on growth and human development. It reviews the trends of foreign direct investment, the opportunities and challenges raised by the emergence of China as buyer of the region's commodities and competitor in the world market, and the transformation of the Latin America from a region of immigration to one of massive emigration. Part IV deals with matters of productive development. At the aggregate level it analyzes issues of technological catching up and divergence as well as different perspectives on the poor productivity and growth performance of the region during recent decades. At the sectoral level, it looks at agricultural policies and performance, the problems and prospects of the energy sector, and the effects on growth of lagging infrastructure development. Part V looks at the social dimensions of development; it analyzes the evolution of income inequality, poverty, and economic insecurity in the region, the evolution of labor markets and the performance of the educational sector, as well as the evolution of social assistance programs and social security reforms in the region. The contributors are leading researchers that belong to different schools of economic thought and most come from countries throughout Latin America, representing a range of views and recognising the diversity of the region. This Handbook is a significant contribution to the field, and will be of interest to academics, graduate students and policy makers interested in economics, political economy, and public policy in Latin America and other developing economies.
Author: Max Kuhn
Publisher: Springer Science & Business Media
Published: 2013-05-17
Total Pages: 595
ISBN-13: 1461468493
DOWNLOAD EBOOKApplied Predictive Modeling covers the overall predictive modeling process, beginning with the crucial steps of data preprocessing, data splitting and foundations of model tuning. The text then provides intuitive explanations of numerous common and modern regression and classification techniques, always with an emphasis on illustrating and solving real data problems. The text illustrates all parts of the modeling process through many hands-on, real-life examples, and every chapter contains extensive R code for each step of the process. This multi-purpose text can be used as an introduction to predictive models and the overall modeling process, a practitioner’s reference handbook, or as a text for advanced undergraduate or graduate level predictive modeling courses. To that end, each chapter contains problem sets to help solidify the covered concepts and uses data available in the book’s R package. This text is intended for a broad audience as both an introduction to predictive models as well as a guide to applying them. Non-mathematical readers will appreciate the intuitive explanations of the techniques while an emphasis on problem-solving with real data across a wide variety of applications will aid practitioners who wish to extend their expertise. Readers should have knowledge of basic statistical ideas, such as correlation and linear regression analysis. While the text is biased against complex equations, a mathematical background is needed for advanced topics.
Author: Eric Scerri
Publisher: Oxford University Press
Published: 2016-10-10
Total Pages: 263
ISBN-13: 0190233001
DOWNLOAD EBOOKIn his latest book, Eric Scerri presents a completely original account of the nature of scientific progress. It consists of a holistic and unified approach in which science is seen as a living and evolving single organism. Instead of scientific revolutions featuring exceptionally gifted individuals, Scerri argues that the "little people" contribute as much as the "heroes" of science. To do this he examines seven case studies of virtually unknown chemists and physicists in the early 20th century quest to discover the structure of the atom. They include the amateur scientist Anton van den Broek who pioneered the notion of atomic number as well as Edmund Stoner a then physics graduate student who provided the seed for Pauli's Exclusion Principle. Another case is the physicist John Nicholson who is virtually unknown and yet was the first to propose the notion of quantization of angular momentum that was soon put to good use by Niels Bohr. Instead of focusing on the logic and rationality of science, Scerri elevates the role of trial and error and multiple discovery and moves beyond the notion of scientific developments being right or wrong. While criticizing Thomas Kuhn's notion of scientific revolutions he agrees with Kuhn that science is not drawn towards an external truth but is rather driven from within. The book will enliven the long-standing debate on the nature of science, which has increasingly shied away from the big question of "what is science?"
Author: Josh Patterson
Publisher: "O'Reilly Media, Inc."
Published: 2017-07-28
Total Pages: 550
ISBN-13: 1491914211
DOWNLOAD EBOOKAlthough interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning—especially deep neural networks—make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their open-source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you’ll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J’s workflow tool Learn how to use DL4J natively on Spark and Hadoop
Author: Sandeep Arora
Publisher: CRC Press
Published: 2021-11-17
Total Pages: 342
ISBN-13: 100006493X
DOWNLOAD EBOOKThis insightful volume opens new horizons for exploring modern therapeutic entities and emerging targets for combating the deadly disease of cancer. The authors provide a review of cancer along with descriptions of its molecular level mechanisms and emphasize the role of promising new therapies, including herbal therapies, that can be utilized for the treatment of metastatic diseases. The chapters look at specific approaches that have been researched and developed and that have almost reached the standardization stage, such as intracellular mechanisms, particularly phosphoprotein-enriched astrocytes and transthyretin proteins; CXCR4; autophagy-inhibiting drugs; spatiotemporal genetic analysis; tyrosine kinase inhibitors; and more. Also considered are advances in diagnostic systems like intra vital microscopy and molecular imaging.
Author: Dànielle Nicole DeVoss
Publisher: Peter Lang Incorporated, International Academic Publishers
Published: 2015
Total Pages: 0
ISBN-13: 9781433125614
DOWNLOAD EBOOKThe symbols, signs, and traces of copyright and related intellectual property laws that appear on everyday texts, objects, and artifacts have multiplied exponentially over the past 15 years. Digital spaces have revolutionized access to content and transformed the ways in which content is porous and malleable. In this volume, contributors focus on copyright as it relates to culture. The editors argue that what «counts» as property must be understood as shifting terrain deeply influenced by historical, economic, cultural, religious, and digital perspectives. Key themes addressed include issues of how: - Culture is framed, defined, and/or identified in conversations about intellectual property; - The humanities and other related disciplines are implicated in intellectual property issues; - The humanities will continue to rub up against copyright (e.g., issues of authorship, authorial agency, ownership of texts); - Different cultures and bodies of literature approach intellectual property, and how competing dynasties and marginalized voices exist beyond the dominant U.S. copyright paradigm. Offering a transnational and interdisciplinary perspective, Cultures of Copyright offers readers - scholars, researchers, practitioners, theorists, and others - key considerations to contemplate in terms of how we understand copyright's past and how we chart its futures.
