A Practical Approach to Timeseries Forecasting Using Python - Graph for TSF Using LSTM

The video tutorial covers the process of converting forecast data into date format and plotting it using the SNS library. It demonstrates how to visualize both the original and forecasted data. The tutorial also discusses the results of an LSTM model with 32 neurons and explores the effects of changing LSTM parameters like epochs and the number of LSTMs on the results.

What is the role of the SNS library in the plotting process?

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Describe the process of creating line plots for the original data and the forecast.

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What changes can be made to the LSTM model to affect the results, according to the text?

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