12 Deep Learning Interview questions you should not be missed (Part 1)
Answer these questions and enter the interview with confidence.
These are questions I often ask when interviewing for an AI Engineer position. In fact, not all interviews need to use all these questions because it depends on the experience and the projects the candidate has done before. Through a lot of interviews, especially with students, I have gathered a collection of 12 most interesting interview questions in Deep Learning and today will share back to you in this article. OK, no more rambling, let’s get started.
1. Presenting the meaning of Batch Normalization
This can be considered a very good question because it covers most of the knowledge that candidates need to know when working with a neural network model. You can answer differently but need to clarify the following main ideas:
Batch Normalization is an effective method when training a neural network model. The goal of this method is to want to normalize the features (the output of each layer after going through the activation) to zero-mean state…
