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Real-Estate-Price-Prediction-
Image detection, voice recognition, audio to text translation, weather forecasting, and other applications rely heavily on machine learning. Machine learning algorithms also produce safe automotive systems and excellent customer service. It is a subset of artificial intelligence, which entails programming computers to understand and solve problems in the same way people do. In this project, I have used the Dataset from Kaggle which contains information (e.g. area type, location) of Bengaluru city of India and I have to predict the price on the basis of the information. For doing analysis I have followed some steps sequentially are given below: Data Cleaning, Feature Engineering, Outlier Remove, Machine Learning Model Building, Linear Regression Model, K-Fold Cross Validation GridsearchCV with Hyperparameter Tuning Predict PriceTowards_Developing_a_Machine_Learning_Model_For_Suicidal_Attempt_Prediction
In this study [N=469], we have classified the samples whohaveattemptedforsuicideandwhodidnot.Forclassification purpose, we have used random forest classifier and we got 83.7% accuracyregardingclassificationofthesetwogroupsofpeople.In addition to our classification analysis, we have also shown which factors can be important for suicidal attemptLove Open Source and this site? Check out how you can help us