GitHub repository: suryakarasala/Machine-Learning-Project
Description: The project uses data from the Weight Lifting Exercises (WLE) Dataset (see http://groupware.les.inf.puc-rio.br/har and also the References section below.) According to the WLE website, six participants were asked to perform one set of 10 repetitions of the Unilateral Dumbbell Biceps Curl in five different fashions, identified as classes A, B, C, D and E. Class A corresponds to a correct execution of the exercise, and the remaining five classes identify common mistakes in this weight lifting exercise. Several sensors were used to collect data about the quality of the exercise execution. The goal of this project is to obtain a prediction algorithm that takes such a set of sensor readings and correctly predicts the corresponding class (A to E). The following analysis uses a random forest prediction algorithm to accomplish this task, after some data cleaning. The results of the analysis confirm that the model provided by this algorithm achieves a high prediction accuracy (as indicated by several prediction quality indicators).