Climate change in India is one of the most alarming problems faced by our community. Due to adverse and sudden changes in climate in past few years, mankind is at threat. Various impacts of climate change include extreme heat, changing rainfall patterns, droughts, groundwater, glacier melt, sea-level rise, and many more. Machine Learning can be used to analyze and predict the graph of change using previous data and thus design a model which in the future can furthermore be used to catalyze impactful work of climate change and take steps in the direction to help India fight against the upcoming climate changes. In this paper, we have analyzed 17 climate change parameters about India. We have applied linear regression, exponential regression, and polynomial regression to the parameters and evaluated the results. Using the designed model, we will predict these parameters for the years 2025,2030, 2035. These predicted values will thus help our community to prevent and take actions against the adverse and hazardous effects on mankind. We have designed and created this model which provides accurate results regarding all 17 parameters. The predicted values will therefore help India to be well equipped against climate change. This data when made available to the people of India will help create awareness among them and will help us save our country from the haphazard effects of climate change.
翻译：印度的气候变化是我们社区面临的最令人震惊的问题之一。由于过去几年来气候的不利和突然变化,人类面临威胁。气候变化的各种影响包括极端热、降雨模式变化、干旱、地下水、冰川融化、海平面上升等等。机器学习可用于利用先前的数据分析和预测变化图,从而设计一个模型,今后还可以用来刺激气候变化的冲击性工作,并朝着帮助印度应对即将到来的气候变化的方向采取步骤。我们在本文件中分析了17个印度的气候变化参数。我们对这些参数应用了线性回归、指数回归和多重回归,并对结果进行了评估。我们将使用设计模型预测这些参数,用于2025、2030和2035年。因此,这些预测值将有助于我们的社区预防和采取行动,对付对人类的不利和危险的影响。我们设计并创建了这一模型,为所有17个参数提供了准确的结果。因此,预测值将有助于印度抵御气候变化。当向印度人民提供这些数据时,我们将帮助他们认识和认识气候变化。
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