Concept Interview Questions

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

Satyam C. - "TF-IDF CONCEPT EXPLANATION AND INTUITION BUILDING: TF-IDF is a measure that reflects the importance of a word in the document relative to a collection of documents. Its full form is Term Frequency - Inverse Document Frequency. The term TF indicates how often a term occurs in a particular document. It is the ratio of count of a particular term in a document to the number of terms in that particular document. So, the intuition is that if a term occurs frequently in a single documen"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

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

Saurabh J. - "The algorithm calculates certain metrics like entropy & Gini Impurity. The goal of the decision tree algorithm is to find the most optimal value for these metrics, lowest values for Gini Impurity & Entropy. Once it converges on the minima, it creates a split & grows the branches."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

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

Matt M. - "Given the dataset does not contain many labels, it implies we cannot directly use supervised learning. I would ask more about the type of dataset we are given. Is it images, text, etc? This may inform the types of transformations we do the dataset. I can see two approaches to training Given the labels we do have, we can find a method to generate labels for the other unlabeled data. This likely will introduce some error since they may not be true labels, but it at least allows processing the"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

Kavithadevi P. - "hash maps work in key value pair. The keys are hashed with a hash algorithm and resulting hashcode(integer) with related value are stored. Accessing a value, removing an element, Searching the hash map: 1) The hash map value can be accessed in O(1) time once you know the key. 2) If the key is not known, the hashmap value can be accessed in O(n) since you have to iterate atleast once. "See full answer

Bhavya V. - "Overfitting is the condition where your model is giving an unexpectedly higher accuracy because of its training in a small database and not getting exposed to anu different type of database while testing"See full answer

Shubhangi S. - "sanity testing, black box testing , white box testing, smoke testing,performance testing"See full answer