"I started asking some questions regarding the constrains of the system:
An antena is emitting a signal that says if the tagged device was out of the room where the interview was happening.
I was able to decide which would be the schema for the Antena's message.
The antena is sending the info of multiple users.
The system doesn't need to push notification to the users when the user left the device behind.
Upon reflection, this is what I recollected doing.
I propuse the json schema a"
Eduardo C. - "I started asking some questions regarding the constrains of the system:
An antena is emitting a signal that says if the tagged device was out of the room where the interview was happening.
I was able to decide which would be the schema for the Antena's message.
The antena is sending the info of multiple users.
The system doesn't need to push notification to the users when the user left the device behind.
Upon reflection, this is what I recollected doing.
I propuse the json schema a"See full answer
"I want to work at Meta because of its reputation as a company that consistently pushes the boundaries of technology, particularly in areas like AI, machine learning, and immersive technologies such as AR and VR. I admire Meta's mission to bring people closer together and create meaningful connections, as well as its focus on long-term innovation, such as the development of the metaverse.
As an AI engineer, I'm excited about the opportunity to work on cutting-edge projects that have a global impa"
Alan T. - "I want to work at Meta because of its reputation as a company that consistently pushes the boundaries of technology, particularly in areas like AI, machine learning, and immersive technologies such as AR and VR. I admire Meta's mission to bring people closer together and create meaningful connections, as well as its focus on long-term innovation, such as the development of the metaverse.
As an AI engineer, I'm excited about the opportunity to work on cutting-edge projects that have a global impa"See full answer
"Scoped out problem constraints - how much data to download, how many computers, and how much time, how you can be detected (decentralized load).
Designed a web crawler."
Faraz A. - "Scoped out problem constraints - how much data to download, how many computers, and how much time, how you can be detected (decentralized load).
Designed a web crawler."See full answer
"In order to earn team members trust you need to show -
1- You need to show them you trust them. Treat others the way you wanted to be treated.
2- Do what you say. Keep commitments.
3- Listen
4- Admit when you make mistakes
5- Consistently make good decisions
"
Ritu G. - "In order to earn team members trust you need to show -
1- You need to show them you trust them. Treat others the way you wanted to be treated.
2- Do what you say. Keep commitments.
3- Listen
4- Admit when you make mistakes
5- Consistently make good decisions
"See full answer
Software Engineer
Behavioral
+1 more
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"While answering such a question, it is important to focus on personal growth, learning, and how the experience improved your teamwork. You want to demonstrate self-awareness, humility, and an ability to adapt.
I had this experience while working on a cross-functional project that involved collaboration between the engineering and marketing teams. In the interview, I shared a story when I misjudged someone and showed unconscious bias towards due their gender, ethnicity or age. It was embarrassin"
Malay K. - "While answering such a question, it is important to focus on personal growth, learning, and how the experience improved your teamwork. You want to demonstrate self-awareness, humility, and an ability to adapt.
I had this experience while working on a cross-functional project that involved collaboration between the engineering and marketing teams. In the interview, I shared a story when I misjudged someone and showed unconscious bias towards due their gender, ethnicity or age. It was embarrassin"See full answer
"DNNs can learn hierarchical features, with each layer learning progressively more abstract features, and generalizes better. SNNs are better for simplier problems involving smaller datasets and if low latency is required."
Louie Z. - "DNNs can learn hierarchical features, with each layer learning progressively more abstract features, and generalizes better. SNNs are better for simplier problems involving smaller datasets and if low latency is required."See full answer
"The company culture is very supportive and collaborative. Googlers are encouraged to be creative and innovative, and there is a lot of freedom to explore new ideas.
The work is challenging and rewarding. Googlers have the opportunity to work on cutting-edge projects that have a real impact on the world.
The company is committed to diversity and inclusion. Google is a great place to work for people from all backgrounds and with all different perspectives.
I am confident that I would b"
Praful B. - "The company culture is very supportive and collaborative. Googlers are encouraged to be creative and innovative, and there is a lot of freedom to explore new ideas.
The work is challenging and rewarding. Googlers have the opportunity to work on cutting-edge projects that have a real impact on the world.
The company is committed to diversity and inclusion. Google is a great place to work for people from all backgrounds and with all different perspectives.
I am confident that I would b"See full answer
"we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"
Kishor J. - "we can use two pointer + set like maintain i,j and also insert jth character to set like while set size is equal to our window j-i+1 then maximize our answer and increase jth pointer till last index"See full answer
"class Node:
def init(self, value):
self.value = value
self.children = []
def inorder_traversal(root):
if not root:
return []
result = []
n = len(root.children)
for i in range(n):
result.extend(inorder_traversal(root.children[i]))
if i == n // 2:
result.append(root.value)
if n == 0:
result.append(root.value)
return result
Example usage:
root = Node(1)
child1 = Node(2)
chil"
Teddy Y. - "class Node:
def init(self, value):
self.value = value
self.children = []
def inorder_traversal(root):
if not root:
return []
result = []
n = len(root.children)
for i in range(n):
result.extend(inorder_traversal(root.children[i]))
if i == n // 2:
result.append(root.value)
if n == 0:
result.append(root.value)
return result
Example usage:
root = Node(1)
child1 = Node(2)
chil"See full answer
"General Approach (using Max-Heap)
Use a max-heap (priority queue) of size k.
For each point:
Compute the distance to P.
Push it into the heap.
If heap size > k, remove the farthest point.
The heap will contain the k closest points to P.
import java.util.*;
public class KClosestPoints {
static class Point {
int x, y;
public Point(int x, int y) { this.x = x; this.y = y; }
// Euclidean distance squared (no need to take square root)
p"
Khushbu R. - "General Approach (using Max-Heap)
Use a max-heap (priority queue) of size k.
For each point:
Compute the distance to P.
Push it into the heap.
If heap size > k, remove the farthest point.
The heap will contain the k closest points to P.
import java.util.*;
public class KClosestPoints {
static class Point {
int x, y;
public Point(int x, int y) { this.x = x; this.y = y; }
// Euclidean distance squared (no need to take square root)
p"See full answer
"We will not always have all the required data to make a decision quickly. We need to work with ambiguity effectively by tying up the available facts with intuition."
Sankar S. - "We will not always have all the required data to make a decision quickly. We need to work with ambiguity effectively by tying up the available facts with intuition."See full answer
"It would have been more interesting to focus on the system design rather than the Trie DS, Interviewee could have just mentioned the Trie and passed to things more important.
Interviewee should have focused on the factors on which he wants to scale the API servers, popularity of the query parts ? region may be ? A hash of many factors ?
Caches should have definitely be discussed, Cache eviction policies, Cache invalidation managements...
Interviewee should have mentioned which kind of API pro"
Aymen D. - "It would have been more interesting to focus on the system design rather than the Trie DS, Interviewee could have just mentioned the Trie and passed to things more important.
Interviewee should have focused on the factors on which he wants to scale the API servers, popularity of the query parts ? region may be ? A hash of many factors ?
Caches should have definitely be discussed, Cache eviction policies, Cache invalidation managements...
Interviewee should have mentioned which kind of API pro"See full answer
"A recursive backtracking solution in python.
def changeSigns(nums: List[int], S: int) -> int:
res = []
n = len(nums)
def backtrack(index, curr, arr):
if curr == S and len(arr) == n:
res.append(arr[:])
return
if index >= len(nums):
return
for i in range(index, n):
add +ve number
arr.append(nums[i])
backtrack(i+1, curr + nums[i], arr)
arr.pop()
"
Yugaank K. - "A recursive backtracking solution in python.
def changeSigns(nums: List[int], S: int) -> int:
res = []
n = len(nums)
def backtrack(index, curr, arr):
if curr == S and len(arr) == n:
res.append(arr[:])
return
if index >= len(nums):
return
for i in range(index, n):
add +ve number
arr.append(nums[i])
backtrack(i+1, curr + nums[i], arr)
arr.pop()
"See full answer