The technical round lasted over an hour, and I was questioned on statistics, machine learning, projects, and python programming. I was asked about hypothesis testing and the p-value in statistics. I was also quizzed on the KNN algorithms in machine learning, containing profound principles linked to it such as Euclidean, Manhattan distance, its applications, how dimensionality reduction affects features, and its implications on KNN. Every project in the project section was also discussed in depth.