Paper Title: Covid-19 Data Analysis And Forecasting

Author's name: Apirajitha P S, Mahalakshmi G, Durai Murugan M

A basic premise of machine learning is to create an algorithm that can take input data, update the output when new data is available, and use statistical analysis to predict the output. Long-term memory is a type of recurrent neural network. Forecasting is an additive, model-based, time-series data forecasting process that adjusts for non-linear trends for year, week, and day seasonality and holiday effects. This works best for time series with strong seasonal influences and for multi-year historical data. Strong prediction of missing data and trend changes, usually with graceful exception handling. Autoregressive Integrated Moving Average (ARIMA) is a statistical analysis model that uses time series data to better understand a data set and predict future trends. Statistical models are autoregressive when they predict future values based on past values.

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