The qualities and patterns found in the data strongly influence the appropriateness of time series and LSTM models. I’ve learned from experience that choosing the best model and fitting it to the dataset are essential to forecasting success. The understanding I obtain from using these models continues to be crucial in forming my viewpoint on sequential data as I progress in my data analysis career.
Beyond traditional statistical techniques, time series forecasting is a crucial analytical technique to uncover trends and patterns concealed inside time-based data. By utilising previous data, interpreting temporal linkages, and forecasting future results, it enables well-informed decision-making.
Time series analysis is essential to data science and forecasting because it provides a window into how events evolve over time. It makes it possible to analyse historical data in order to find