"If 0's aren't a concern, couldn't we just
multiply all numbers.
and then divide product by each number in the list ?
if there's more than one zero, then we just return an array of 0s
if there's one zero, then we just replace 0 with product and rest 0s.
what am i missing?"
Sachin R. - "If 0's aren't a concern, couldn't we just
multiply all numbers.
and then divide product by each number in the list ?
if there's more than one zero, then we just return an array of 0s
if there's one zero, then we just replace 0 with product and rest 0s.
what am i missing?"See full answer
"As an interviewer, I have asked this question to candidates in the past. Here are the major topics I am looking for in an interview
The candidate should understand that there are ways of measuring the loss of a particular clustering. For example, we can take the average distance of each point to it's cluster center.
The candidate should understand that this loss will always decrease as the number of clusters increases. For that reason, we can't just pick the value of K that minimizes the l"
Michael F. - "As an interviewer, I have asked this question to candidates in the past. Here are the major topics I am looking for in an interview
The candidate should understand that there are ways of measuring the loss of a particular clustering. For example, we can take the average distance of each point to it's cluster center.
The candidate should understand that this loss will always decrease as the number of clusters increases. For that reason, we can't just pick the value of K that minimizes the l"See full answer
"A few months ago I joined a micro-services platform engineering team as their manager, at that time my team was struggling to deliver towards an upcoming production deadline for a customer facing product. Production date had been moved 5 times already and there were about 40% of product features which were remaining to be tested and signed off to move to production . I was made responsible to deliver the release of this product within the deadline and turnaround the software delivery throughput."
Shuchi A. - "A few months ago I joined a micro-services platform engineering team as their manager, at that time my team was struggling to deliver towards an upcoming production deadline for a customer facing product. Production date had been moved 5 times already and there were about 40% of product features which were remaining to be tested and signed off to move to production . I was made responsible to deliver the release of this product within the deadline and turnaround the software delivery throughput."See full answer
"Write a function which Caesar ciphers all the strings so that the first character is "a". Use ascii code points and the modulo operator to do this.
Use this function to create a hashmap between each string and the CC-a string. Then go through each key:value pair in the hashmap, and use the CC-a ciphered value as the key in a new defaultdict(list), adding the original string to the value field in the output."
Michael B. - "Write a function which Caesar ciphers all the strings so that the first character is "a". Use ascii code points and the modulo operator to do this.
Use this function to create a hashmap between each string and the CC-a string. Then go through each key:value pair in the hashmap, and use the CC-a ciphered value as the key in a new defaultdict(list), adding the original string to the value field in the output."See full answer
Machine Learning Engineer
Coding
+1 more
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"\# Definition for a binary tree node.
class TreeNode:
def init(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Solution:
def maxPathSum(self, root: TreeNode) -> int:
self.max_sum = float('-inf')"
Jerry O. - "\# Definition for a binary tree node.
class TreeNode:
def init(self, val=0, left=None, right=None):
self.val = val
self.left = left
self.right = right
class Solution:
def maxPathSum(self, root: TreeNode) -> int:
self.max_sum = float('-inf')"See full answer
"Problem: Given an input string txt consisting of alphanumeric characters and the parentheses characters '(' & ')', write a function which removes the minimum number of characters to return a version of the string with properly balanced parenthesis.
Answer: You can do this with a counter.
Psuedo-Python
Start with counter = 0
output = []
Iterate through the string, every time you encounter a '(', increment the counter. Add the character to the output.
If you encounter a ')', decrement the coun"
Michael B. - "Problem: Given an input string txt consisting of alphanumeric characters and the parentheses characters '(' & ')', write a function which removes the minimum number of characters to return a version of the string with properly balanced parenthesis.
Answer: You can do this with a counter.
Psuedo-Python
Start with counter = 0
output = []
Iterate through the string, every time you encounter a '(', increment the counter. Add the character to the output.
If you encounter a ')', decrement the coun"See full answer
"Even more faster and vectorized version, using np.linalg.norm - to avoid loop and np.argpartition to select lowest k. We dont need to sort whole array - we need to be sure that first k elements are lower than the rest.
import numpy as np
def knn(Xtrain, ytrain, X_new, k):
distances = np.linalg.norm(Xtrain - Xnew, axis=1)
k_indices = np.argpartition(distances, k)[:k] # O(N) selection instead of O(N log N) sort
return int(np.sum(ytrain[kindices]) > k / 2.0)
`"
Dinar M. - "Even more faster and vectorized version, using np.linalg.norm - to avoid loop and np.argpartition to select lowest k. We dont need to sort whole array - we need to be sure that first k elements are lower than the rest.
import numpy as np
def knn(Xtrain, ytrain, X_new, k):
distances = np.linalg.norm(Xtrain - Xnew, axis=1)
k_indices = np.argpartition(distances, k)[:k] # O(N) selection instead of O(N log N) sort
return int(np.sum(ytrain[kindices]) > k / 2.0)
`"See full answer
"My leadership style is flexible and adaptive, it varies depending on the team members and the needs of the company. My leadership goal is to empower the team and inspire and grow leaders. In order to achieve that, I combine transformational, democratic and coaching leadership styles.
Usually when we are facing a new type of challenge, or at the early stage of a project, I like to adapt the transformational leadership which allows me to listen to all the suggestions from the team members and sta"
onering2ruleall - "My leadership style is flexible and adaptive, it varies depending on the team members and the needs of the company. My leadership goal is to empower the team and inspire and grow leaders. In order to achieve that, I combine transformational, democratic and coaching leadership styles.
Usually when we are facing a new type of challenge, or at the early stage of a project, I like to adapt the transformational leadership which allows me to listen to all the suggestions from the team members and sta"See full answer
"function findPrimes(n) {
if (n < 2) return [];
const primes = [];
for (let i=2; i <= n; i++) {
const half = Math.floor(i/2);
let isPrime = true;
for (let prime of primes) {
if (i % prime === 0) {
isPrime = false;
break;
}
}
if (isPrime) {
primes.push(i);
}
}
return primes;
}
`"
Tiago R. - "function findPrimes(n) {
if (n < 2) return [];
const primes = [];
for (let i=2; i <= n; i++) {
const half = Math.floor(i/2);
let isPrime = true;
for (let prime of primes) {
if (i % prime === 0) {
isPrime = false;
break;
}
}
if (isPrime) {
primes.push(i);
}
}
return primes;
}
`"See full answer
"
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
"
import java.util.*;
class Solution {
// Time Complexity: O(n^2)
// Space Complexity: O(n)
public static List> threeSum(int[] nums) {
// Ensure that the array is sorted first
Arrays.sort(nums);
// Create the results list to return
List> results = new ArrayList();
// Iterate over the length of nums
for (int i = 0; i < nums.length-2; i++) {
// We will have the first number in"
Victor O. - "
import java.util.*;
class Solution {
// Time Complexity: O(n^2)
// Space Complexity: O(n)
public static List> threeSum(int[] nums) {
// Ensure that the array is sorted first
Arrays.sort(nums);
// Create the results list to return
List> results = new ArrayList();
// Iterate over the length of nums
for (int i = 0; i < nums.length-2; i++) {
// We will have the first number in"See full answer
"Over-fitting of a model occurs when model fails to generalize to any new data and has high variance withing training data whereas in under fitting model isn't able to uncover the underlying pattern in the training data and high bias.
Tree based model like decision tree and random forest are likely to overfit whereas linear models like linear regression and logistic regression tends to under fit.
There are many reasons why a Random forest can overfits easily 1. Model has grown to its full depth a"
Jyoti V. - "Over-fitting of a model occurs when model fails to generalize to any new data and has high variance withing training data whereas in under fitting model isn't able to uncover the underlying pattern in the training data and high bias.
Tree based model like decision tree and random forest are likely to overfit whereas linear models like linear regression and logistic regression tends to under fit.
There are many reasons why a Random forest can overfits easily 1. Model has grown to its full depth a"See full answer
"class ListNode:
def init(self, val=0, next=None):
self.val = val
self.next = next
def has_cycle(head: ListNode) -> bool:
slow, fast = head, head
while fast and fast.next:
slow = slow.next
fast = fast.next.next
if slow == fast:
return True
return False
debug your code below
node1 = ListNode(1)
node2 = ListNode(2)
node3 = ListNode(3)
node4 = ListNode(4)
creates a linked list with a cycle: 1 -> 2 -> 3 -> 4"
Anonymous Roadrunner - "class ListNode:
def init(self, val=0, next=None):
self.val = val
self.next = next
def has_cycle(head: ListNode) -> bool:
slow, fast = head, head
while fast and fast.next:
slow = slow.next
fast = fast.next.next
if slow == fast:
return True
return False
debug your code below
node1 = ListNode(1)
node2 = ListNode(2)
node3 = ListNode(3)
node4 = ListNode(4)
creates a linked list with a cycle: 1 -> 2 -> 3 -> 4"See full answer