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This paper focuses on developing a weather prediction model to predict temperature and humidity. Further, a classification model is also extended to predict the weather condition using the expected model’s output. The proposed hybrid model can predict the temperature and humidity and forecast future weather conditions. The prediction and classification models are created using neural networks and k-nearest neighbors, respectively. The prediction model’s results have shown the best ability for both the output variables (temperature and humidity) with R2 values close to one and MSE values close to zero. Further, the classification model’s results also showed better execution in classifying the weather conditions with the highest accuracy values.

The objective of this research is to devise a cognitive behavioral therapy system or a Therapy Chatbot capable of catering to the health and informative needs of a user. Also, the key focus is on the therapy element which detects the level of depression in a particular individual. With the increasing stress in day to day life, every individual is prone to depression and the consequences of depression are disastrous, therefore this study revolves around helping people against depression using technology. Since depression has been the major cause of suicide among people, hence, an attempt to lessen the chances of depression and thereby suicide has been made. This study is intended to target 300 million people worldwide. The system not only detects the level of depression in an individual but also suggests remedies to lower the level of depression in an individual. Apart from this, the system caters to the informative needs of the user by helping him make a search for name, place, things, check weather conditions etc. This study uses python as the base language which can be integrated with android so as to serve as a messaging platform so that it can target a larger audience. It is designed in such a way that it can emulate a psychotherapist.