Machine Learning Engineer Interview Questions

Exponent - "We've identified the problem as a Design a Product question. Use the following framework for tackling these types of questions: Ask Clarifying Questions Identify users, behaviors, and pain points State product goal Identify current solutions Brainstorm new solutions Evaluate solutions Measure success Summarize We'll go through each of these step by step. Ask Clarifying Questions The PM interview isn't about your ability to come up w"See full answer

Sanmitra I. - "BERT is a bidirectional encoder representation transformer. It takes a sequence of tokens and produces vector embeddings for each token. The BERT Model was trained on the task of next sentence prediction task and masked language modeling. The key difference between word2vec and BERT is that, word2vec produces semantic embeddings for each word, where as BERT produces contextual word embeddings based on the relationships between surrounding words. Example - Vector Embedding of lets say word "i"See full answer

Tiago R. - "class TrieNode { constructor() { this.children = {}; this.isEndOfWord = false; } } class Trie { constructor() { this.root = new TrieNode(); } insert(word) { let node = this.root; for (const char of word) { if (!node.children[char]) { node.children[char] = new TrieNode(); } node = node.children[char]; } node.isEndOfWord = true; } search(word) { l"See full answer

Zain R. - "I've worked on projects not quite like this, but very similar, in the past - I'll borrow from that to answer this: The Broader Context this problem doesn't specify the type of data we're working with, or how it's being ingested to align with my personal background, I'll assume a picture that lends this problem well to being a computer vision (abbreviated "CV") related question: let's say we have a conveyor belt in a waste facility, which sequentially carries a stream of waste w"See full answer

Ankit R. - "i use google frequently, but most of the time i use for syntax and terms which i dont undestand, google is my go to guy."See full answer

Shibin P. - "A typical computer vision pipeline consists of several key stages that process and analyze visual data to extract meaningful information. Here’s a general outline of the steps involved: Image Acquisition:Capturing images or videos using cameras or other imaging devices. Preprocessing steps such as resizing, cropping, and converting color spaces. Image Preprocessing:Noise reduction (e.g., using filters like Gaussian blur). Image normalization to standardize pixel values. Contrast e"See full answer

Vishwanath K. - "DevOps Engineer Interview Questions for 3+ yrs experience candidate"See full answer

Divya R. - "static boolean sudokuSolve(char board) { return sudokuSolve(board, 0, 0); } static boolean sudokuSolve(char board, int r, int c) { if(c>=board[0].length) { r=r+1; c=0; } if(r>=board.length) return true; if(boardr=='.') { for(int num=1; num<=9; num++) { boardr=(char)('0' + num); if(isValidPosition(board, r, c)) { if(sudokuSolve(board, r, c+1)) return true; } boardr='.'; } } else { return sudokuSolve(board, r, c+1); } return false; } static boolean isValidPosition(char b"See full answer

Ayush B. - "focus was on tradeoffs of diff object detection algorithms, data collection and labelling, foundational models, followup: not working well in production, retraining/active learning"See full answer

Anonymous Roadrunner - "from typing import List def traprainwater(height: List[int]) -> int: if not height: return 0 l, r = 0, len(height) - 1 leftMax, rightMax = height[l], height[r] res = 0 while l < r: if leftMax < rightMax: l += 1 leftMax = max(leftMax, height[l]) res += leftMax - height[l] else: r -= 1 rightMax = max(rightMax, height[r]) "See full answer