<ul data-eligibleForWebStory="false"><li>Time series data is prevalent in various domains, ranging from stock prices to health monitoring, characterized by data points with timestamps.</li><li>Traditional statistical models like ARIMA and Prophet are effective for basic trends but struggle with noisy, nonlinear, and multivariate data.</li><li>Deep learning techniques, especially LSTMs (Long Short-Term Memory networks), excel at handling time series data with long dependencies and real-world complexities.</li><li>Reinforcement learning, typically used in game AI, can also be applied to time series forecasting for making decisions like stock trading.</li></ul>

Time Series Is Everywhere—Here’s How to Actually Forecast It

Discover more