Interview Questions

Techzen I. - "Implemented the Java code to find the largest island. It is similar to count the island. But in this we need to keep track of max island and compute its perimeter."See full answer

Deepak K. - "FN Given text need to figure out is it following guidelines. Should notify the user in case of not following guidelines. Reason for failure should have misleading/spam/adult filters. NFN High availability High Scalability Low latency of processing Estimations 1M requests/min text - 10kb => 9.5GB/min => 14TB/day API fetchmoderationscore(text) score will be between 0 to 1 more than 0.8 => not following guidelines fetchmoderationscore(text, filter)"See full answer

Ina K. - "HashMap supports insert, search, delete and retrieve in O(1). It stores data as key value pairs."See full answer

Tiago R. - "function isValid(s) { const stack = []; for (let i=0; i < s.length; i++) { const char = s.charAt(i); if (['(', '{', '['].includes(char)) { stack.push(char); } else { const top = stack.pop(); if ((char === ')' && top !== '(') || (char === '}' && top !== '{') || (char === ']' && top !== '[')) { return false; } } } return stack.length === 0"See full answer

Hari priya K. - "Hey Grandma, you've had a lot of experience with infants, haven't you? When they were babies, you taught them how to chew in their first six months. This initial phase is like giving them data. Once they learned how to chew, they could handle any food you gave them. Next, you refined their learning by teaching them that they should only chew on food. This is like refining the data so they understand what is relevant. Then, a few months later, they started crawling and walking, learning by observ"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