What Is Time Series Forecasting?

From anticipating equipment failures to optimizing airline schedules, time series forecasting helps you uncover patterns in data, make predictions, and make more informed decisions. In this demonstration, you will explore: - How to prepare messy time series data - Key challenges such as missing values, trends, and seasonality - Signal processing with wavelets for complex patterns - Statistical methods such as regression and ARIMA - Machine learning techniques such as support vector regression - Deep learning methods such as LSTMs and transformers No single approach works for every scenario. Throughout the demonstration, guidance is provided on what time series forecasting methods might work for your data. You’ll also learn about tools in MATLAB® that make it easy to experiment with different time series forecasting techniques. Learn more: https://www.youtube.com/watch?v=sro-BtpwKyE https://www.youtube.com/watch?v=W57zL51NGUg Related Resources: What Is Time Series Analysis?: https://www.mathworks.com/discovery/time-series-analysis.html What Is Data Preprocessing?: https://www.mathworks.com/discovery/data-preprocessing.html What Is Data Cleaning?: https://www.mathworks.com/discovery/data-cleaning.html -------------------------------------------------------------------------------------------------------- Get a free product trial: https://goo.gl/ZHFb5u Learn more about MATLAB: https://goo.gl/8QV7ZZ Learn more about Simulink: https://goo.gl/nqnbLe See what's new in MATLAB and Simulink: https://goo.gl/pgGtod © 2025 The MathWorks, Inc. MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See www.mathworks.com/trademarks for a list of additional trademarks. Other product or brand names may be trademarks or registered trademarks of their respective holders.