Abstract
This paper explores three machine learning models for weather prediction namely Support Vector Machine (SVM), Artificial Neural Network(ANN) and a Time Series based Recurrent Neural Network (RNN). It also discussed the steps followed to achieve results. RNN using time series along with a linear SVC and a five-layered neural network is used to predict the weather. The results of these models are analyzed and compared on the basis of Root Mean Squared Error between the predicted and actual values. For weather Forecasting, this paper uses Pandas, NumPy, Keras, Git, Matplotlib, TensorFlow, Anaconda and Google Cloud Services. It is found that Time Series based RNN does the best job of predicting the weather
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