Time series analysis in machine learning involves studying data points collected or recorded at specific time intervals to identify patterns, trends, or seasonality. This method helps forecast future values based on past behavior, making it highly valuable in fields like finance, weather prediction, healthcare, and sales forecasting. By understanding the structure of temporal data, businesses can make informed decisions, improve efficiency, and anticipate future outcomes with greater accuracy. Techniques such as ARIMA and LSTM are commonly used for time-based modeling. To gain hands-on skills in this area, consider enrolling in a data science machine learning course.
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