Concept Interview Questions

Yasin E. - "25 min"See full answer

T I. - "Idempotence refers to the property that the same request multiple times produces the same result on the server side. No matter how many times I repeat the request, the server state does not change after the first request. This concept is important to ensure consistency, especially in systems where requests may be repeated due to network failures or other problems. Let's take a look at different HTTP methods for a clearer understanding. GET: By definition, GET requests must be powerless. Execut"See full answer

1036 loknadh R. - "No ,MSE is suitable for only regression modes. Although the logistic regression in Its name has regression , but it is a classification problem so MSE is not suitable for classification models like logistic regression."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

Shibin P. - "Effective loss functions for computer vision models vary depending on the specific task, some commonly used loss functions for different tasks: Classification Cross-Entropy Loss:Used for multi-class classification tasks. Measures the difference between the predicted probability distribution and the true distribution. Binary Cross-Entropy Loss:Used for binary classification tasks. Evaluates the performance of a model by comparing predicted probabilities to the true binary labe"See full answer

Asish B. - "Number of employees after the first year = n*(1+r) = n1 Number of employees after the second year = n1(1+r) = n(1+r)**2 Hence, the number of employees after 't' years = n(1+r)*t"See full answer

Sri V. - "Switching from a linear kernel to RBF / Gaussian kernel is likely to result in overfitting the model. It is a move that adds complexity to the mix, and if the data doesn't need that sort of complexity, it would result in overfitting. On the other hand, all the other three approaches would only try too reduce complexity in the process, thereby doesn't contribute to overfitting the model."See full answer

Aziz V. - "ArrayList allows constant time access (O(1)) to elements using their index because it uses a dynamic array internally, whereas LinkedList requires traversal from the head node, resulting in linear time complexity (O(n))."See full answer

Harsh S. - "AUC 0.5 equates to a random model, so when creating any machine learning model or statistical model, you ideally want your model to at least beat this random baseline."See full answer

Sue G. - "Race Condition i,e multiple threads modifying simultaneously can lead to data inconsistency Operations like putIfAbsent() or computeIfAbsent() are not atomoic i.e duplicate entries or missing updates when multiple threads perform operations Data Corruption : during resizing of a hashmap by a thread, if another thread is accessing the same data , buckets can get corrupted, leading to a loss of data"See full answer

Exponent - "This is a Measure Success question with a slight twist. The twist here is we need to consider a hypothetical product rather that one already built. This changes our formula slightly - specifically we may not be able to apply a UX flow to drive analysis since we're unsure of the implementation. Instead, we'll look at core behaviors that are indicative of success. Here's the modified formula: Ask clarifying questions State the goal of the feature **Apply a UX flow to drive a"See full answer

Lash - "A perceptron is the most basic building block of a neural network and represents a single-layer binary classifier."See full answer