"The height of a binary tree is the maximum number of edges from the root node to any leaf node. To calculate the height of a binary tree, we can use a recursive approach. The basic idea is to compare the heights of the left and right subtrees of the root node, and return the maximum of them plus one."
Prashant Y. - "The height of a binary tree is the maximum number of edges from the root node to any leaf node. To calculate the height of a binary tree, we can use a recursive approach. The basic idea is to compare the heights of the left and right subtrees of the root node, and return the maximum of them plus one."See full answer
"This is another Fermi problem — an estimation or approximation problem with limited information and back-of-the-envelope calculations. There's no right answer: interviewers want to understand how you think and how well you can explain your reasoning, rather than what you already know.
Recall the formula for Fermi problems:
Ask clarifying questions
Catalog what you know
Make equation(s)
Think about edge cases to add to equation
**Breakdown components of your"
Exponent - "This is another Fermi problem — an estimation or approximation problem with limited information and back-of-the-envelope calculations. There's no right answer: interviewers want to understand how you think and how well you can explain your reasoning, rather than what you already know.
Recall the formula for Fermi problems:
Ask clarifying questions
Catalog what you know
Make equation(s)
Think about edge cases to add to equation
**Breakdown components of your"See full answer
"Question: An array of n integers is given, and a positive integer k, where k << n. k indicates that the absolute difference between each element's current index (icurrent) and the index in the sorted array (isorted) is less than k (|icurr - isorted| < k).
Sort the given array.
The most common solution is with a Heap:
def solution(arr, k):
min_heap = []
result = []
for i in range(len(arr))
heapq.heappush(min_heap, arr[i])
"
Guilherme M. - "Question: An array of n integers is given, and a positive integer k, where k << n. k indicates that the absolute difference between each element's current index (icurrent) and the index in the sorted array (isorted) is less than k (|icurr - isorted| < k).
Sort the given array.
The most common solution is with a Heap:
def solution(arr, k):
min_heap = []
result = []
for i in range(len(arr))
heapq.heappush(min_heap, arr[i])
"See full answer
"untuk mengurutkan daftar angka secara efisien saya akan menggunakan aplikasi pengolah angka yaitu excel dengan rumus rumus untuk mempermudah dan mempercepat pengurutan daftar angka"
Isnadea soraya R. - "untuk mengurutkan daftar angka secara efisien saya akan menggunakan aplikasi pengolah angka yaitu excel dengan rumus rumus untuk mempermudah dan mempercepat pengurutan daftar angka"See full answer
"This is a Fermi problem — an estimation or approximation problem with limited information and back-of-the-envelope calculations. There's no right answer: interviewers want to understand how you think and how well you can explain your reasoning, rather than what you already know.
Recall the formula for Fermi problems:
Ask clarifying questions
Catalog what you know
Make equation(s)
Think about edge cases to add to equation
**Breakdown components of your equat"
Exponent - "This is a Fermi problem — an estimation or approximation problem with limited information and back-of-the-envelope calculations. There's no right answer: interviewers want to understand how you think and how well you can explain your reasoning, rather than what you already know.
Recall the formula for Fermi problems:
Ask clarifying questions
Catalog what you know
Make equation(s)
Think about edge cases to add to equation
**Breakdown components of your equat"See full answer
"First, I would operationalize the term "slip" by asking:
What’s slipping — delivery, scope, quality, or decision-making?
Second, I would ask the following questions that help me shape the possible causes for the "slip":
What is important for us in this project delivery: time/quality/scope?
What is the priory of this project? Is it urgent? Do we have a strict customer or other stakeholder commitment?
Is it a big project that involves multiple teams or is only one team involved"
Anastasiia V. - "First, I would operationalize the term "slip" by asking:
What’s slipping — delivery, scope, quality, or decision-making?
Second, I would ask the following questions that help me shape the possible causes for the "slip":
What is important for us in this project delivery: time/quality/scope?
What is the priory of this project? Is it urgent? Do we have a strict customer or other stakeholder commitment?
Is it a big project that involves multiple teams or is only one team involved"See full answer
"This is a Technical question. It tests your ability to understand high level technical concepts. Even though your job won't have any coding involved, you'll still need to understand these concepts. Being able to cover all these topics with clarity communicates confidence in your interviewer.
Unfortunately, there's no formula for technical questions, but some general tips are:
Use analogies when you can
Break your solution into clear, bite-size steps
Don't be afraid to use examples to b"
Exponent - "This is a Technical question. It tests your ability to understand high level technical concepts. Even though your job won't have any coding involved, you'll still need to understand these concepts. Being able to cover all these topics with clarity communicates confidence in your interviewer.
Unfortunately, there's no formula for technical questions, but some general tips are:
Use analogies when you can
Break your solution into clear, bite-size steps
Don't be afraid to use examples to b"See full answer
"Hadoop is better than PySpark when you are dealing with extremely large scale, batch oriented, non-iterative workloads where in-memory computing isn't feasible/ necessary, like log storage or ETL workflows that don't require high response times. It's also better in situations where the Hadoop ecosystem is already deeply embedded and where there is a need for resource conscious, fault tolerant computation without the overhead of Spark's memory constraints. In these such scenarios, Hadoop's disk-b"
Joshua R. - "Hadoop is better than PySpark when you are dealing with extremely large scale, batch oriented, non-iterative workloads where in-memory computing isn't feasible/ necessary, like log storage or ETL workflows that don't require high response times. It's also better in situations where the Hadoop ecosystem is already deeply embedded and where there is a need for resource conscious, fault tolerant computation without the overhead of Spark's memory constraints. In these such scenarios, Hadoop's disk-b"See full answer