• Hands on experience in Linear Regression, Logistic Regression, Decision Tree, Random forest, XGboost and SVM.(Hands on experience is basically on projects).
• Hands on experience in unsupervised learning using K-means clustering and hierarchical clustering.
• Time Series analysis using - Hot winters, AR, MA and ARIMA.
• Data visualization in R using ggplot2 and plot for interactive graphs.
• Feature engineering in R and SAS. Missing value and outlier handling, Transforming variable, creating new variables, creating dummy variables, reshaping data using packages like dplyr and tidyr in R.
• Good understanding of ROC, AUC, KS, Accuracy and lift performance matrix.