MANU JOSEPH

Ayyan Mani is a man born to greater things, which wouldn't surprise his neighbours in the vast tenement building in which he lives, where to be sober and employed practically makes a man a legend. He works as an assistant at the Institute of Theory and Research, where he studies with amusement and envy the public battles and private love affairs of the squabbling scientists. But when an opportunity for betterment presents itself in the form of his 'gifted' ten-year-old son Adi, father and son embark on an outrageous ruse that will have far-reaching consequences ...Manu Joseph's archly comic debut is a tale of a man's attempt to elevate himself and his family above the banality of ordinary existence.

á"Ayyan Mani llevaba el espeso pelo negro peinado hacia un lado, dividido por una raya irregular hecha sin cuidado, como la línea divisoria que los británicos solían trazar entre dos barrios enemigos. La mirada era penetrante y sagaz. Un poblado bigote ocultaba su permanente sonrisa. Un hombre moreno vestido con pulcritud, pero con ropa un tanto barata". aAyyan trabaja en el Instituto de Teoria e Investigacion Mumbai. Es el asistente personal de un insufrible astronomo y director del instituto, Arvind Acharya que esta obsesionado con la teoria de que microscopicos extraterrestres caen continuamente a la Tierra desde el cielo. aAtrapado en una vida anodina sabe que no puede escapar de su realidad, por lo que para entretenerse y alegrar la vida de su mujer adicta a las telenovelas, teje una ficcion en torno a su hijo de diez años que provoca una cadena de acontecimientos extraordinarios que es incapaz de detener.aPor otro lado, una guerra se gesta entre los cientificos rivales en el Instituto y una hermosa astrobiologa complica aun mas las cosas. El sigue de cerca los acontecimientos e inventa una forma de promover su propia causa.

Build real-world time series forecasting systems which scale to millions of time series by applying modern machine learning and deep learning conceptsKey FeaturesExplore industry-tested machine learning techniques used to forecast millions of time seriesGet started with the revolutionary paradigm of global forecasting modelsGet to grips with new concepts by applying them to real-world datasets of energy forecastingBook DescriptionWe live in a serendipitous era where the explosion in the quantum of data collected and a renewed interest in data-driven techniques such as machine learning (ML), has changed the landscape of analytics, and with it, time series forecasting. This book, filled with industry-tested tips and tricks, takes you beyond commonly used classical statistical methods such as ARIMA and introduces to you the latest techniques from the world of ML.This is a comprehensive guide to analyzing, visualizing, and creating state-of-the-art forecasting systems, complete with common topics such as ML and deep learning (DL) as well as rarely touched-upon topics such as global forecasting models, cross-validation strategies, and forecast metrics. You'll begin by exploring the basics of data handling, data visualization, and classical statistical methods before moving on to ML and DL models for time series forecasting. This book takes you on a hands-on journey in which you'll develop state-of-the-art ML (linear regression to gradient-boosted trees) and DL (feed-forward neural networks, LSTMs, and transformers) models on a real-world dataset along with exploring practical topics such as interpretability.