Introduction to Time Series Forecasting with Tensorflow and InfluxDB

This article introduces time series forecasting with TensorFlow and InfluxDB. Time series data is unique in that it has autocorrelation, meaning data points are correlated with each other. This makes working with time series data for machine learning different compared to other domains. The author explains the use of TensorFlow, an open-source framework for machine learning created by Google, and InfluxDB, a purpose-built database for storing and working with time series data. They also discuss the differences between machine learning models and statistical models in terms of their suitability for forecasting tasks. The article concludes with a discussion on why TensorFlow is a good choice for working with time series data and how InfluxDB can simplify many problems related to data engineering and the overall data pipeline.