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This book introduces practical seismic analysis techniques and evaluation of interpretation confidence, for graduate students and industry professionals - independent of commercial software products.
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THE INSTANT NEW YORK TIMES BESTSELLER "Sims’s vivid portrait of Trump shrewdly balances admiration with misgivings, and his intricate, engrossing accounts of White House vendettas and power plays have a good mix of immersion and perspective. The result is one of the best of the recent flood of Trump tell-alls." —Publishers Weekly The first honest insider’s account of the Trump administration. If you hate Trump you need the truth; if you love Trump you need the truth. After standing at Donald Trump’s side on Election Night, Cliff Sims joined him in the West Wing as Special Assistant to the President and Director of White House Message Strategy. He soon found himself pulled into the Pr...
International bestselling author Fforde invites fans to return to the witty, wizardly world of the Chronicles of Kazam with the fabulous follow-up to "The Last Dragonslayer."
Uma verdadeira Enciclopédia do Direito do Trabalho! A Revista LTr é uma valiosa fonte de estudos e informações sobre doutrina, jurisprudência e legislação do Direito do Trabalho. Publicação mensal, editada há mais de 80 anos ininterruptamente. Abrange toda Legislação Trabalhista do período; Doutrina elaborada e assinada por eminentes especialistas em Direito do Trabalho; Jurisprudência Trabalhista, acórdãos na íntegra dos Tribunais Superiores e Regionais. Repositório autorizado para indicação de julgados no STF e no TST. As informações são organizadas de modo a tornar mais ágil a localização da matéria e a consulta de modo geral. São editados índices semestrais: ...
This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.