Depression and anxiety are two different versions of mood disorders. It is a state in which people used to develop some deep side effects. Depression and Anxiety can develop some serious effects on individual in terms of both physical and mental emotions. It’s main feature is sadness in extreme measures, and can often lead to suicides and mental traumas. Depression is a major illness that affect human minds in a worst sequence. According to a report by WHO (World Health Organisations) , dated June 2019-2020 , India is the most depressed country in the world, due to Covid situations and financial problems with 7% of its total population being traumatized of mental problems. And to take this problem as an illness, the first thing to do is analyzing the main difference . According to Anxiety and Depression Association of America (ADAA) anxiety and depression are the most common mental illness among people around United States. If you don’t treat your anxiety disorder you will soon develop some extreme psychological disorders and later suffer with depression . Depression cause people to have sad mood, loss of interest , low esteem , bad taste , sleeping attacks etc. Our application mainly contains mental health problem quiz questionnaire to detect the early symptoms. But this analysis can be deceived easily if a patient tried to answer differently. Hence, we come here to provide one way method to treat and detect depression and anxiety detection using Machine Learning Algorithms. We obtain major questionnaire in the form of quizzes , and users fill it on basis of their mental emotions. This machine learning data is used to analyze the early detection of mental traumas on normal people. This algorithm takes readings of emotions from the answer of quizzes given by the specific user. Classification machine learning algorithm used K nearest neighbour, Naive Bayes theorem, Decision Tree Algorithm and Random Forest classifier have been used for the detection model, Word Clouds to differentiate the positive and negative words. After all the final results the user is immediately warned of their depression level, and they are urged to get professional help given by our website. The overall model not only achieves high accuracy due to its Machine Learning Approach model , but also inherits the scalability regarding one proper input size.