El barómetro es un instrumento de medición atmosérica, específicamente utilizado en la determinación de la fuerza por unidad de superficie ejercida por el peso de la atmósfera. Existe un gran número de equipos atmoféricos con distintos tipos de estos aparátos y son diariamente utilizados ya que la presión atmosférica juega un papel importante en la determinación y pronóstico del tiempo así como en el área de investigación al momento de realizarse experimentos ya que pueden llegar a afectar o hacer variar el funcionamiento de muchos aparatos electrónicos y mecánicos.
Deedy CV/Resume
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Linear regression is one of the most widely used statistical methods available today. It is used by data analysts and students in almost every discipline. However, for the standard ordinary least squares method, there are several strong assumptions made about data that is often not true in real world data sets. This can cause numerous problems in the least squares model. One of the most common issues is a model overfitting the data. Ridge Regression and LASSO are two methods used to create a better and more accurate model. I will discuss how overfitting arises in least squares models and the reasoning for using Ridge Regression and LASSO include analysis of real world example data and compare these methods with OLS and each other to further infer the benefits and drawbacks of each method.
This paper introduces the risks associated with the development of Artificial General Intelligence (AGI), gives an overview of the major organizations involved in the study of AGI risk, and examines current actions being taken with respect to AGI risk management. It then discusses possible AGI public policy options and their likely outcomes, and finally recommends a set of policies designed to decrease the risk presented by AGI.
Chris Nota
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