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“Deep learning is making a good wave in delivering a solution to difficult problems that have been faced in the field of artificial intelligence (AI) for so many years, as quoted by Yann LeCun, Yoshua Bengio & Geoffrey Hinton.”
For a data scientist to successfully apply deep learning, they must first understand how to apply the mathematics of modeling, choose the right algorithm to fit your model to the data, and come up with the right technique to implement.
Preparing for an interview is not easy. There is significant uncertainty regarding the data science interview questions you will be asked. No matter how much work experience or what data science certificate you have, an interviewer can throw you off with a set of questions that you didn’t expect.
During a data science interview, the interviewer will ask questions spanning a wide range of topics, requiring both strong technical knowledge and solid communication skills from the interviewee. Your statistics, programming, and data modeling skills will be put to the test through a variety of questions and question styles that are intentionally designed to keep you on your feet and force you to demonstrate how you operate under pressure.