Machine Learning Interview Questions

What is OOB error and how does it occur? For each bootstrap sample, there is one-third of data that was not used in the creation of the tree, i.e., it was out of the sample. This data is referred to as out of bag data. In order to get an unbiased measure of the accuracy … Read more

Explain the differences between Random Forest and Gradient Boosting machines. Random forests are a significant number of decision trees pooled using averages or majority rules at the end. Gradient boosting machines also combine decision trees but at the beginning of the process unlike Random forests. Random forest creates each tree independent of the others while … Read more

What’s the trade-off between bias and variance? Bias is error due to erroneous or overly simplistic assumptions in the learning algorithm you’re using. This can lead to the model underfitting your data, making it hard for it to have high predictive accuracy and for you to generalize your knowledge from the training set to the … Read more

Do you have experience with Spark or big data tools for machine learning? You’ll want to get familiar with the meaning of big data for different companies and the different tools they’ll want. Spark is the big data tool most in demand now, able to handle immense datasets with speed. Be honest if you don’t … Read more

Is ARIMA model a good fit for every time series problem? No, ARIMA model is not suitable for every type of time series problem. There are situations where ARMA model and others also come in handy. ARIMA is best when different standard temporal structures require to be captured for time series data. What is inductive … Read more