Time series data

Time series data is composed of sequential measurements collected over successive time intervals. This type of data is prevalent across diverse fields such as finance, healthcare, meteorology, and energy, tracking everything from stock prices to patient vital signs and weather conditions. Its unique characteristic is the dependency of observations on time, often revealing trends, seasonal patterns, cycles, and occasional abrupt changes or anomalies. In machine learning, time series data offers a fertile ground for predictive modeling, providing both challenges due to its temporal nature and opportunities for deep analysis and forecasting.