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Published Paper Details:
Paper Title
Weather Forecasting with Machine Learning Using Python
Authors
Teesa Reddy, Ashish reddy, Jyothika
Keywords
ML,python,Weather forcast
Abstract
Accurate weather forecasting is essential for various applications, including agriculture, disaster management, and daily planning. This study explores the use of machine learning techniques to predict weather conditions using Python. By leveraging historical weather data, we employ several machine learning algorithms, such as linear regression, decision trees, random forests, and neural networks, to develop predictive models. The data is preprocessed to handle missing values and normalized to ensure efficient training. Feature engineering techniques are applied to extract significant patterns and trends. The models are evaluated based on their predictive accuracy, using metrics like mean squared error (MSE) and R-squared values. Our results demonstrate that machine learning can provide reliable and accurate weather forecasts, with some models outperforming traditional statistical methods.
IJCRT's Publication Details
Unique Identification Number - IJCRT2407339
Paper ID - 265615
Page Number(s) - c904-c906
Pubished in - Volume 12 | Issue 7 | July 2024
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Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882
E-ISSN Number - 2320-2882
Cite this article
Teesa Reddy, Ashish reddy, Jyothika, "Weather Forecasting with Machine Learning Using Python", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.12, Issue 7, pp.c904-c906, July 2024, Available at :http://www.ijcrt.org/papers/IJCRT2407339.pdf
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Volume 14 | Issue 2
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Submit Manuscript Online Impact Factor: 7.97 Review Results : Within 02-03 Days Paper Publication : Within 02-03 Days
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ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
ISSN and 7.97 Impact Factor Details
ISSN: 2320-2882 Impact Factor: 7.97 and ISSN APPROVED Journal Starting Year (ESTD) : 2013
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