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Title: The Unreasonable Effectiveness of Data Speaker: Peter Norvig (Google Research) In decades past, models of human language were wrought from the sweat and pencils of linguists. In the modern day, it is more common to think of language modeling as an exercise in probabilistic inference from data: we observe how words and combinations of words are used, and from that build computer models of what the phrases mean. This approach is hopeless with a small amount of data, but somewhere in the range of millions or billions of examples, we pass a threshold, and the hopeless suddenly becomes effective, and computer models sometimes meet or exceed human performance. This talk gives examples of the data available in large repositories: text, images, videos, and even the interactions of students in a massive online class, and shows what can be done with the data. Link: http://techfest.uc3m.es/2013/?event=intervencion-de-peter-norvig-director-de-investigacion-de-google
Tres de los artífices de esta tercera edición de T3chFest charlan sobre cómo han conseguido hacerla posible.
José Manuel Ortega, desarrollador de frontend y backend
Título: Processing Real-Time Big Data with Storm Ponente: Javier Antoniucci Link: https://techfest.uc3m.es/programa/processing-real-time-big-data-with-storm/ ¿Cómo hace Spotify para hacer 100.000 sugerencias musicales por segundo? Apache Storm es un modelo de programación e infraestructura de ejecución para el procesamiento distribuido de Eventos. Intentaremos sintetizar sus conceptos principales, describir un caso de uso clásico y compartir las conclusiones de nuestras experiencias.