Time Series

A time series is a sequence of data points collected or recorded at specific time intervals.

It is used when there is a need to analyze data that changes over time, such as stock prices, weather data, or sensor readings. Time series data is commonly applied in scenarios such as forecasting, anomaly detection, and trend analysis. The technique works by capturing the temporal dependencies and patterns in the data, allowing for the prediction of future values based on past observations.

For example, in stock price prediction, a time series model can be used to forecast future stock prices based on historical price data. In weather forecasting, time series data can be used to predict future weather conditions based on past weather patterns.

Time series analysis is important because it allows for the understanding and prediction of temporal patterns in data. It is a powerful approach in machine learning, enabling models to make informed predictions and decisions based on time-dependent data.