作者：Jeremy CuruksuForecasting the evolution of events over time is essential to many applications, such as option pricing, disease progression, speech recognition, and supply chain management. It is also notoriously difficult: The goal is not just to predict an overall outcome but instead a precise sequence of events that will happen at specific times. Niels Bohr, a physics Nobel laureate, famously said that “prediction is very difficult, especially if it’s about the future.” In this blog post I will explore advanced techniques for time series forecasting using deep learning approaches on AWS. The post focuses on arbitrary time series value prediction so will be of interest to any reader working with time series. The post assumes that the reader already possesses basic technical knowledge in the field of Machine Learning. In this post, I will show you how to develop an
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