Milan Laboratories India Private Limited Interview Questions, Process, and Tips

Developed a predictive model for customer churn using machine learning algorithms

• Used R programming language to clean and preprocess customer data

• Implemented various machine learning algorithms such as Random Forest and Logistic Regression

• Evaluated model performance using metrics like accuracy, precision, and recall

I use metrics such as accuracy, precision, recall, F1 score, ROC-AUC, and confusion matrix to test the models deployed.

• Accuracy: measures the overall correctness of the model

• Precision: measures the proportion of true positive predictions among all positive predictions

• Recall: measures the proportion of true positive predictions among all actual positives

• F1 score: balances precision and recall

• ROC-AUC: measures the area u...read more

I have a basic understanding of JavaScript and can work with it to some extent.

• Familiar with basic JavaScript syntax and concepts

• Able to manipulate DOM elements using JavaScript

• Have experience working with JavaScript libraries like jQuery

Yes, R can be integrated with JavaScript using the 'shiny' package to create interactive web applications.

• Use the 'shiny' package in R to create interactive web applications

• Use the 'htmlwidgets' package to embed interactive R visualizations in web pages

• Utilize the 'r2d3' package to create D3 visualizations in R and embed them in web applications

The 'V8' package in R is used to import and execute JavaScript code.

• Use the 'V8' package in R to import and execute JavaScript code.

• Install the 'V8' package using install.packages('V8').

• Load the 'V8' package using library(V8).

• Use the v8() function to create a new V8 context and execute JavaScript code.