Concept Interview Questions

Sonia M. - "virtual function is a member function declared with virtual keyword in a base class. It enables derived classes to redefine this function with their own specific implementations."See full answer

Susmita S. - "Function that is passed as an argument or parameter to another function and it gets executed when the function that it is passed to gets executed"See full answer

Yasin E. - "25 min"See full answer

William M. - "Relu = 0 if > some threshold else x sigmoid normalizes to 0-1 asymptotically"See full answer

Niteesh V. - "inheritance means its acquire all properties from parent class to child class.composition means its acquire some properties as our request is called composition"See full answer

Erjan G. - "a process can include many threads. good for concurrent and parallel task execution"See full answer

Yasir M. - "Open Oriented programming is a way to organize code around objects rather then functions."See full answer

Alan T. - "The difference between convex and nonconvex functions lies in their mathematical properties and the implications for optimization problems. Convex Functions:A convex function has a shape where any line segment connecting two points on its graph lies entirely above or on the graph. This property ensures that any local minimum is also a global minimum, making optimization straightforward and reliable. Convex functions are critical in machine learning and optimization tasks because of th"See full answer

Sue G. - "In Java, GC is the process of automatically identifying and reclaming memory occupied by objects that are no longer reachable.. the process involves the 3 steps Mark phase -- identify the objects that are still in use. i.e reachable sweep Phase -- removes the unreachable objects compact phase -- rearragnes objects to prevent fragmentation 4 types of Garbage collection Serial GC -- single threaded simple and compacting -- best for small applications Parrallel GC -- throughput GC"See full answer

Woosung J. - "For a dataset with one million data points, a Deep Neural Network (DNN) is almost always the superior choice over a K-Nearest Neighbors (KNN) algorithm. The primary reasons for this preference involve computational efficiency, scalability, and the ability to handle high-dimensional data. 1. Computational Complexity (Inference Time) KNN: It is a "lazy learner." It doesn't actually "learn" a model; instead, it stores the entire dataset. To make a single prediction, it must calcul"See full answer