LinkedIn Machine Learning Engineer Interview Questions

Review this list of 24 LinkedIn machine learning engineer interview questions and answers verified by hiring managers and candidates.
  • LinkedIn logoAsked at LinkedIn 
    Video answer for 'Edit distance'
    +16

    "from collections import deque def updateword(words, startword, end_word): if end_word not in words: return None # Early exit if end_word is not in the dictionary queue = deque([(start_word, 0)]) # (word, steps) visited = set([start_word]) # Keep track of visited words while queue: word, steps = queue.popleft() if word == end_word: return steps # Found the target word, return steps for i in range(len(word)): "

    叶 路. - "from collections import deque def updateword(words, startword, end_word): if end_word not in words: return None # Early exit if end_word is not in the dictionary queue = deque([(start_word, 0)]) # (word, steps) visited = set([start_word]) # Keep track of visited words while queue: word, steps = queue.popleft() if word == end_word: return steps # Found the target word, return steps for i in range(len(word)): "See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +3 more
  • LinkedIn logoAsked at LinkedIn 
    +16

    "We can use dictionary to store cache items so that our read / write operations will be O(1). Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1) Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"

    Alfred O. - "We can use dictionary to store cache items so that our read / write operations will be O(1). Each time we read or update an existing record, we have to ensure the item is moved to the back of the cache. This will allow us to evict the first item in the cache whenever the cache is full and we need to add new records also making our eviction O(1) Instead of normal dictionary, we will use ordered dictionary to store cache items. This will allow us to efficiently move items to back of the cache a"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +6 more
  • +2

    "Traverse the array of points while computing the distance and pushing it to the heap. Then traverse again the heap and pop the k closest. Time O(nlogn) Space O(n)"

    Dadja Z. - "Traverse the array of points while computing the distance and pushing it to the heap. Then traverse again the heap and pop the k closest. Time O(nlogn) Space O(n)"See full answer

    Machine Learning Engineer
    Coding
    +2 more
  • LinkedIn logoAsked at LinkedIn 
    Video answer for 'Merge Intervals'
    +35

    "const mergeIntervals = (intervals) => { const compare = (a, b) => { if(a[0] b[0]) return 1 else if(a[0] === b[0]) { return a[1] - b[1] } } let current = [] const result = [] const sorted = intervals.sort(compare) for(let i = 0; i = b[0]) current[1] = b[1] els"

    Kofi N. - "const mergeIntervals = (intervals) => { const compare = (a, b) => { if(a[0] b[0]) return 1 else if(a[0] === b[0]) { return a[1] - b[1] } } let current = [] const result = [] const sorted = intervals.sort(compare) for(let i = 0; i = b[0]) current[1] = b[1] els"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +6 more
  • LinkedIn logoAsked at LinkedIn 
    +15

    "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"

    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

    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
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  • LinkedIn logoAsked at LinkedIn 
    Video answer for 'Find the median of two sorted arrays.'
    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • LinkedIn logoAsked at LinkedIn 
    Video answer for 'Explain Bayes' theorem.'

    "Is it bad to get the answer a different way? Will they mark that as not knowing Bayes Theorem or just correct as it is an easier way to get the answer? The way I went is to look at what happens when the factory makes 100 light bulbs. Machine A makes 60 of which 3 are faulty, Machine B makes 40 of which 1.2 are faulty. Therefore the pool of faulty lightbulbs is 3/4.2 = 5/7 from machine A and 1.2/4.2 = 3/7 from Machine B."

    Will I. - "Is it bad to get the answer a different way? Will they mark that as not knowing Bayes Theorem or just correct as it is an easier way to get the answer? The way I went is to look at what happens when the factory makes 100 light bulbs. Machine A makes 60 of which 3 are faulty, Machine B makes 40 of which 1.2 are faulty. Therefore the pool of faulty lightbulbs is 3/4.2 = 5/7 from machine A and 1.2/4.2 = 3/7 from Machine B."See full answer

    Machine Learning Engineer
    Concept
    +2 more
  • LinkedIn logoAsked at LinkedIn 
    Video answer for 'Implement k-means clustering.'

    "i dont know"

    Dinesh K. - "i dont know"See full answer

    Machine Learning Engineer
    Coding
    +5 more
  • LinkedIn logoAsked at LinkedIn 
    Video answer for 'Given an nxn grid of 1s and 0s, return the number of islands in the input.'
    +10

    " from typing import List def getnumberof_islands(binaryMatrix: List[List[int]]) -> int: if not binaryMatrix: return 0 rows = len(binaryMatrix) cols = len(binaryMatrix[0]) islands = 0 for r in range(rows): for c in range(cols): if binaryMatrixr == 1: islands += 1 dfs(binaryMatrix, r, c) return islands def dfs(grid, r, c): if ( r = len(grid) "

    Rick E. - " from typing import List def getnumberof_islands(binaryMatrix: List[List[int]]) -> int: if not binaryMatrix: return 0 rows = len(binaryMatrix) cols = len(binaryMatrix[0]) islands = 0 for r in range(rows): for c in range(cols): if binaryMatrixr == 1: islands += 1 dfs(binaryMatrix, r, c) return islands def dfs(grid, r, c): if ( r = len(grid) "See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • LinkedIn logoAsked at LinkedIn 
    Video answer for 'Merge k sorted linked lists.'
    +6

    "A much better solution than the one in the article, below: It looks like the ones writing articles here in Javascript do not understand the time/space complexity of javascript methods. shift, splice, sort, etc... In the solution article you have a shift and a sort being done inside a while, that is, the multiplication of Ns. My solution, below, iterates through the list once and then sorts it, separately. It´s O(N+Log(N)) class ListNode { constructor(val = 0, next = null) { th"

    Guilherme F. - "A much better solution than the one in the article, below: It looks like the ones writing articles here in Javascript do not understand the time/space complexity of javascript methods. shift, splice, sort, etc... In the solution article you have a shift and a sort being done inside a while, that is, the multiplication of Ns. My solution, below, iterates through the list once and then sorts it, separately. It´s O(N+Log(N)) class ListNode { constructor(val = 0, next = null) { th"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • LinkedIn logoAsked at LinkedIn 
    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • LinkedIn logoAsked at LinkedIn 
    Machine Learning Engineer
    Behavioral
    +1 more
  • LinkedIn logoAsked at LinkedIn 
    +17

    " O(n) time, O(1) space from typing import List def maxsubarraysum(nums: List[int]) -> int: if len(nums) == 0: return 0 maxsum = currsum = nums[0] for i in range(1, len(nums)): currsum = max(currsum + nums[i], nums[i]) maxsum = max(currsum, max_sum) return max_sum debug your code below print(maxsubarraysum([-1, 2, -3, 4])) `"

    Rick E. - " O(n) time, O(1) space from typing import List def maxsubarraysum(nums: List[int]) -> int: if len(nums) == 0: return 0 maxsum = currsum = nums[0] for i in range(1, len(nums)): currsum = max(currsum + nums[i], nums[i]) maxsum = max(currsum, max_sum) return max_sum debug your code below print(maxsubarraysum([-1, 2, -3, 4])) `"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • Machine Learning Engineer
    System Design
  • Machine Learning Engineer
    Coding
    +1 more
  • LinkedIn logoAsked at LinkedIn 
    +6

    "function isPalindrome(s, start, end) { while (s[start] === s[end] && end >= start) { start++; end--; } return end <= start; } function longestPalindromicSubstring(s) { let longestPalindrome = ''; for (let i=0; i < s.length; i++) { let j = s.length-1; while (s[i] !== s[j] && i <= j) { j--; } if (s[i] === s[j]) { if (isPalindrome(s, i, j)) { const validPalindrome = s.substring(i, j+1"

    Tiago R. - "function isPalindrome(s, start, end) { while (s[start] === s[end] && end >= start) { start++; end--; } return end <= start; } function longestPalindromicSubstring(s) { let longestPalindrome = ''; for (let i=0; i < s.length; i++) { let j = s.length-1; while (s[i] !== s[j] && i <= j) { j--; } if (s[i] === s[j]) { if (isPalindrome(s, i, j)) { const validPalindrome = s.substring(i, j+1"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +3 more
  • LinkedIn logoAsked at LinkedIn 
    +2

    "Make current as root. 2 while current is not null, if p and q are less than current, go left. If p and q are greater than current, go right. else return current. return null"

    Vaibhav D. - "Make current as root. 2 while current is not null, if p and q are less than current, go left. If p and q are greater than current, go right. else return current. return null"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +4 more
  • LinkedIn logoAsked at LinkedIn 

    " First, sort the array in ascending order. This ensures that we can easily check the triangle inequality condition. Use a loop to iterate through the array. For each triplet of consecutive elements, check if they satisfy the triangle inequality condition a+b>ca+b>c. As soon as you find a valid tuple, return it. If no valid tuple is found, return null. This approach is efficient with a time complexity of O(nlog⁡n)O(nlogn) due to the sorting step, followed by a linear scan of the array"

    Shivam P. - " First, sort the array in ascending order. This ensures that we can easily check the triangle inequality condition. Use a loop to iterate through the array. For each triplet of consecutive elements, check if they satisfy the triangle inequality condition a+b>ca+b>c. As soon as you find a valid tuple, return it. If no valid tuple is found, return null. This approach is efficient with a time complexity of O(nlog⁡n)O(nlogn) due to the sorting step, followed by a linear scan of the array"See full answer

    Machine Learning Engineer
    Data Structures & Algorithms
    +1 more
  • LinkedIn logoAsked at LinkedIn 
    Machine Learning Engineer
    Concept
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