Search results for ""author sergio ramírez""

Adiós Muchachos is a candid insider’s account of the leftist Sandinista revolution in Nicaragua. During the 1970s, Sergio Ramírez led prominent intellectuals, priests, and business leaders to support the Sandinista National Liberation Front (FSLN), against Anastasio Somoza’s dictatorship. After the Sandinistas overthrew the Somoza regime in 1979, Ramírez served as vice-president under Daniel Ortega from 1985 until 1990, when the FSLN lost power in a national election. Disillusioned by his former comrades’ increasing intolerance of dissent and resistance to democratization, Ramírez defected from the Sandinistas in 1995 and founded the Sandinista Renovation Movement. In Adiós Muchachos, he describes the utopian aspirations for liberation and reform that motivated the Sandinista revolution against the Somoza regime, as well as the triumphs and shortcomings of the movement’s leadership as it struggled to turn an insurrection into a government, reconstruct a country beset by poverty and internal conflict, and defend the revolution against the Contras, an armed counterinsurgency supported by the United States. Adiós Muchachos was first published in 1999. Based on a later edition, this translation includes Ramírez’s thoughts on more recent developments, including the re-election of Daniel Ortega as president in 2006.

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This book offers a comprehensible overview of Big Data Preprocessing, which includes a formal description of each problem. It also focuses on the most relevant proposed solutions. This book illustrates actual implementations of algorithms that helps the reader deal with these problems. This book stresses the gap that exists between big, raw data and the requirements of quality data that businesses are demanding. This is called Smart Data, and to achieve Smart Data the preprocessing is a key step, where the imperfections, integration tasks and other processes are carried out to eliminate superfluous information. The authors present the concept of Smart Data through data preprocessing in Big Data scenarios and connect it with the emerging paradigms of IoT and edge computing, where the end points generate Smart Data without completely relying on the cloud.Finally, this book provides some novel areas of study that are gathering a deeper attention on the Big Data preprocessing. Specifically, it considers the relation with Deep Learning (as of a technique that also relies in large volumes of data), the difficulty of finding the appropriate selection and concatenation of preprocessing techniques applied and some other open problems.Practitioners and data scientists who work in this field, and want to introduce themselves to preprocessing in large data volume scenarios will want to purchase this book. Researchers that work in this field, who want to know which algorithms are currently implemented to help their investigations, may also be interested in this book.

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