“…An expert group with representatives from national statistical bodies was formed to develop the technical components of the project and start compiling data at national level. …”

“…It also includes shorter reviews of policy developments in Austria, Denmark, Germany, Greece, the United Kingdom and the United States, as well as energy balances and key statistical data for all Member countries and key energy statistics for the past 20 years. …”

“…The Patents Manual, issued in 1994, provides information on how patent data can be used as indicators, and also shows how these can be linked to other statistics on science, technology and economic activity (R&D, scientific publications, trade, production, etc.)…”

“…These developments have been associated with a number of other worrying statistics, including low intergenerational social mobility and weak real income growth for many households. …”

“…Responding to renewed interest in nuclear energy, this Nuclear Energy Outlook uses the most current data and statistics available and provides projections up to 2050 to consider growth scenarios and potential implications on the future use of nuclear energy. …”

Tabla de Contenidos: “…COVER -- PREFACE -- ABOUT THE OECD -- REFORMING THE OECD -- OECD IN 2000: SELECTED EVENTS -- OVERVIEW: OECD Priority activities -- ECONOMIC GROWTH AND STABILITY -- THE SOURCES OF GROWTH -- DIGITAL DIVIDE -- TERRITORIAL DEVELOPMENT POLICY COMMITTEE (TDPC) -- EMPLOYMENT AND SOCIAL COHESION -- A QUESTION OF HEALTH -- AGEING -- TRADE AND INTERNATIONAL INVESTMENT -- TRADE AND CORE LABOUR STANDARDS -- GUIDELINES FOR MULTINATIONAL ENTERPRISES -- SUSTAINABLE DEVELOPMENT -- SUSTAINABLE AGRICULTURE -- CLIMATE CHANGE -- GOVERNANCE -- COMBATING CARTELS -- HARMFUL TAX PRACTICES -- BEST USE OF NEW TECHNOLOGIES -- MANAGING RISK -- FOOD SAFETY -- DEVELOPMENT -- A BETTER WORLD FOR ALL: PROGRESS TOWARDS -- CLUB DU SAHEL -- CO-OPERATIVE RELATIONS RELATIONS WITH NON-MEMBER ECONOMIES -- PRIVATE SECTOR DEVELOPMENT CENTRE -- CHINA -- RUSSIA -- STATISTICS -- PUBLIC AFFAIRS AND COMMUNICATIONS -- BIAC AND TUAC -- FORUM 2000 -- OECD OBSERVER -- EXECUTIVE DIRECTORATE -- REDEVELOPMENT OF THE OECD HEADQUARTERS SITE -- HOW THE OECD WORKS -- NUCLEAR ENERGY AGENCY -- INTERNATIONAL ENERGY AGENCY -- EUROPEAN CONFERENCE OF MINISTERS OF TRANSPORT www.oecd.org/cem/ -- THE INTERNATIONAL FIGHT AGAINST MONEY LAUNDERING: THE FATF www.oecd.org/fatf/ -- OECD ORGANISATION CHART -- MARCH 2001 -- OECD COUNCIL MEETING AT MINISTERIAL LEVEL COMMUNIQUEI.: SHAPING GLOBALISATION -- THE OECD SECRETARIAT -- AMBASSADORS, permanent represeNtatives to the oecd (march 2001)…”

“…This special edition includes the commitments reported by Members of the OECD's Development Assistance Committee (DAC) as well as statistical tables which provide a more comprehensive picture. …”

“…The police, the judiciary, and entire local and departmental governments are rife with criminal infiltrators; murder statistics have surpassed civil-war levels in recent years; criminal operatives brazenly assassinate government officials and troublesome members of the political class; and broad swaths of territory are now effectively under the control of criminal groups. …”

“…This volume contributes to the reconstruction of this quite unknown period of Fermi's life, marked however by the publication of the Fermi statistics, a scientific breakthrough which would bring the Italian scientist to international celebrity thanks to its application in several fields of physics. …”

“…A basic familiarity with undergraduate level mathematics and statistics is expected but not strictly required. A basic knowledge of Scala is required as well as the ability to write simple Scala programs. …”

“…This has the practical coverage of statistics and machine learning. You will develop knowledge to build statistical models and machine learning systems in Julia with attractive visualizations. …”

“…Basic knowledge of Python programming, statistics, and linear algebra is assumed. What You Will Learn Acquire, format, and visualize your data Build an image-similarity search engine Generate meaningful visualizations anyone can understand Get started with analyzing social network graphs Find out how to implement sentiment text analysis Install data analysis tools such as Pandas, MongoDB, and Apache Spark Get to grips with Apache Spark Implement machine learning algorithms such as classification or forecasting In Detail Beyond buzzwords like Big Data or Data Science, there are a great opportunities to innovate in many businesses using data analysis to get data-driven products. …”

“…Prior knowledge of basic SQL command is also required What You Will Learn Learn different features and offering on the latest Hive Understand the working and structure of the Hive internals Get an insight on the latest development in Hive framework Grasp the concepts of Hive Data Model Master the key concepts like Partition, Buckets and Statistics Know how to integrate Hive with other frameworks such as Spark, Accumulo, etc In Detail Hive was developed by Facebook and later open sourced in Apache community. …”

“…Scala will be a valuable tool to have on hand during your data science journey for everything from data cleaning to cutting-edge machine learning About This Book Build data science and data engineering solutions with ease An in-depth look at each stage of the data analysis process - from reading and collecting data to distributed analytics Explore a broad variety of data processing, machine learning, and genetic algorithms through diagrams, mathematical formulations, and source code Who This Book Is For This learning path is perfect for those who are comfortable with Scala programming and now want to enter the field of data science. Some knowledge of statistics is expected. What You Will Learn Transfer and filter tabular data to extract features for machine learning Read, clean, transform, and write data to both SQL and NoSQL databases Create Scala web applications that couple with JavaScript libraries such as D3 to create compelling interactive visualizations Load data from HDFS and HIVE with ease Run streaming and graph analytics in Spark for exploratory analysis Bundle and scale up Spark jobs by deploying them into a variety of cluster managers Build dynamic workflows for scientific computing Leverage open source libraries to extract patterns from time series Master probabilistic models for sequential data In Detail Scala is especially good for analyzing large sets of data as the scale of the task doesn't have any significant impact on performance. …”

“…Written for both beginner and intermediate JMP users working in or studying health care, Data Management and Analysis Using JMP: Health Care Case Studies bridges the gap between taking traditional statistics courses and successfully applying statistical analysis in the workplace. …”

“…Devised as a “how-to” guide, it offers a mix of theory and practice while adding new and timely topics to its core chapters, including prevention by design, product stewardship, statistics for safety and health, safety and health management systems, safety and health management of international operations, and EHS auditing. …”

“…Master an array of machine learning techniques with real-world projec.ts that interface TensorFlow with R, H2O, MXNet, and other languages Key Features Gain expertise in machine learning, deep learning, and predictive modeling techniques Build intelligent end-to-end projects for finance, social media, and a variety of other domains Implement multi-class classification, regression, and clustering in your models Book Description R is one of the most popular languages when it comes to exploring the mathematical side of machine learning and easily performing computational statistics. This Learning Path shows you how to leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization. …”

“…You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. …”

“…Understand how the query optimizer works Troubleshoot queries using extended events, SQL trace, dynamic management views (DMVs), the data collector, and other tools Work with query operators for data access, joins, aggregations, parallelism, and updates Speed up queries and dramatically improve application performance by creating the right indexes Understand statistics and how to detect and fix cardinality estimation errors Maximize OLTP query performance using In-Memory OLTP (Hekaton) features, including memory-optimized tables and natively compiled stored procedures Monitor and promote plan caching and reuse to improve application performance Improve the performance of data warehouse queries using columnstore indexes Handle query processor limitations with hints and other methods…”