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@article{152525,
        author = {Prof. S.B. Nikam and Akhil Aditya and Tanish Jain and Yashraj Tandon},
        title = {Analysis of Covid-19 (India) Using Machine Learning Algorithms},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {8},
        number = {3},
        pages = {676-681},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=152525},
        abstract = {In light of recent events, such as the coronavirus pandemic, prediction algorithms based on machine learning (ML) have proven effective in  predicting  perioperative  outcomes  and  improving  decision-making  in  the  future. Machine learning models have long been used in many application areas  that  need  to  detect  and prioritize  negative threat characteristics. Typically, a variety of forecasting methods are used to address forecasting problems. This study shows how machine learning algorithms can predict the  number  of patients  who will be  infected by COVID19, a virus that is now considered a possible threat to humans. In this study, the following predictive model are used to predict COVID19 risk factors: Linear Regression, Exponential Time Smoothing, Autoregressive Integrated Moving Average (ARIMA). The results of the study indicate that these strategies are a viable option in the current COVID19 pandemic.},
        keywords = {COVID, Machine Learning},
        month = {},
        }