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Give a drawback of gradient descent ?
Logistic regression gives probabilities as a result then how do we use it to predict a binary outcome?
What is adagrad algorithm in machine learning?
What kind of problems lend themselves to machine learning?
What is the difference between supervised and unsupervised learning?
Which one would you prefer to choose – model accuracy or model performance?
What are standardization and normalisation?
What is bias-variance trade-off in machine learning?
Does 100% precision mean that our model predicts all the values correctly?
Why do we convert categorical variables into factor? Which function is used in r to perform the same?
How much data will you allocate for your training, validation and test sets?
Tell me what is a recommendation system?
Tell us how do classification and regression differ?
Tell us what evaluation approaches would you work to gauge the effectiveness of a machine learning model?
Explain me what cross-validation technique would you use on a time series dataset?
