Interview Questions

Ishan S. - "I can see that Gen Z (born between 1995 and 2009) needs a redesigned washing machine with a busier life than ever, newer living arrangements, and a longer time frame. Let's try and understand why we need a new product for Gen Z: Clarifying question - 1) Do we have a specific goal while redesigning the machine? Should we optimize for speed, space, or functionalities? (Assume - No) 2) Do we have geographical constraints? Countries have different power and electrical thresholds, which can decide"See full answer

Jyoti V. - "Over-fitting of a model occurs when model fails to generalize to any new data and has high variance withing training data whereas in under fitting model isn't able to uncover the underlying pattern in the training data and high bias. Tree based model like decision tree and random forest are likely to overfit whereas linear models like linear regression and logistic regression tends to under fit. There are many reasons why a Random forest can overfits easily 1. Model has grown to its full depth a"See full answer

Rahul M. - "We should define automated Scheduled Updates for deployment to keep the application up to date."See full answer

Jake M. - "Random Forest is a machine learning model used for classification problems or regression problems. It can handle binary classification as well as multi-class classification. It is a very efficient model and is great for a baseline or used in a service that needs extremely low latency depending on the size of the model. It's also a good option for wide datasets (dataset with many features) due to it's random subset of features. it is slightly less optimized for deep datasets on very large dataset"See full answer