摘要：
In this post we’re going to work with time series data, and write R functions to aggregate hourly and daily time series in monthly time series to catch a glimpse of their underlying patterns. For this analysis we’re going to use public meteorological data recorded by the government of the Argentinian province of San Luis. Data about rainfalls, temperature, humidity and in some cases winds, is published in the REM website (Red de Estaciones Meteorológicas, http://www.clima.edu.ar/). Also, here you can download meteorological data (in .csv format) that has been recorded by weather stations around different places from San Luis.
摘要： 生成對抗網絡一直是非常美妙且高效的方法，自 14 年 Ian Goodfellow 等人提出第一個生成對抗網絡以來，各種變體和修正版如雨後春筍般出現，它們都有各自的特性和對應的優勢。本文介紹了主流的生成對抗網絡及其對應的 PyTorch 和 Keras 實現代碼，希望對各位讀者在 GAN 上的理解與實現有所幫助。
摘要： Google Finance no longer provides data for historical prices or financial statements, so we say goodbye to getSymbols.google() and getFinancials.google(). (#221) They are now defunct as of quantmod 0.4-13.
摘要： How do Bitcoin markets behave? What are the causes of the sudden spikes and dips in cryptocurrency values? Are the markets for different altcoins inseparably linked or largely independent? How can we predict what will happen next?
