Using a one year multivariate dataset consisting of eight columns, develop a LSTM model along with Hilbert Huan Transform (using Empirical Mode Decomposition) in making one day prediction. That is, by using datasets of 365 days, we use the data of 364 days to train, test & validate model and then predict the generation (first column) for 365th day ( i.e for 31 Dec 2019 having 96 datapoints). Compare actual versus predicted using data, matplot and calculating Mean Absolute Error, RMSE etc for the same.
Condition: Project to be completed within two days , codes will be made using jupyter note book, codes explained and payment made after completion only.
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