You have a dataset containing information about customers, including demographic data (age, gender, income), transaction history (amount spent, number of purchases), and other relevant metrics. How would you approach building a predictive model to forecast future customer behavior, such as the likelihood of making a large purchase or churn risk?
Walk us through a project. What statistical methods did you use? How did you do feature engineering? How did you decide which features to use? How would you handle a conflict?
talk about project on resume
all the basic interview questions like what is pca, xgboost, rf and differences between algorithms etc.
Can you explain Deep Learning to laymen? Can you explain the details of one of your projects?
Why I use specific approach while working on my ML project?
Tell me about yourself, why do you want to work a motorola
Was based on tools and techniques mentioned in CV.
Case Study : How would you present your case findings in terms of business information to the marketing team
One of the questions was When to use regularization?
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