Quality of low Resource Time Series Prediction
Time series data are prevalent in many scientific and engineering disciplines. Time series forecasting is a crucial task in modeling time series data, and is an important area of machine learning In this research work, we have been investigating time series prediction using low quality resources. We have tried to understand how we can get maximum from resources with low quality and try to implement different time series prediction models. In This work we have used LSTM and Transformer(with Time2Vec) to predict chaotic nature of Lorenz attractor.