Amazon Interview Questions

Onesimo F. - "N/A. I never had the same experience."See full answer

Nathan B. - " This is mostly correct and fairly fast. My code has a bug somewhere where it fails on cases like the last case, where there are negative number on both ends of the array and the sums . from collections import deque debug = True # False def prdbg(*x): global debug debug = True # False if debug: print(x) else: return def max_sum(arr, start, end): if type(arr) == type(''' "See full answer

Midde V. - "Front Page Layout Design for Newspaper App Header Section Logo: Displays at the top left. App Name: Displays alongside, so very prominent. Search Bar: Centered with search to find articles within the application. Navigation Menu: The links to the respective sections, World, Politics, Sports, Entertainment, and Opinion, etc Main Content Area Top Stories Carousel: It is a rotating banner that displays the top 3-5 news stories with images along with their headlines. Each story should be cl"See full answer

Joshua B. - "reaching my goal and going to the limits"See full answer

T I. - "This is due to sticky sessions. The load balancer is not correctly configured with sticky session option. It is likely the servers were storing session data on the server themselves (in-memory), and thus when user makes a request, the load balancer routes this to a different server than the one they started with, that second server may not recognise the user's session. This could prompt the user to log in again. One way to resolve this, is to use a centralised session storage, something like"See full answer

Shibin P. - "Effective loss functions for computer vision models vary depending on the specific task, some commonly used loss functions for different tasks: Classification Cross-Entropy Loss:Used for multi-class classification tasks. Measures the difference between the predicted probability distribution and the true distribution. Binary Cross-Entropy Loss:Used for binary classification tasks. Evaluates the performance of a model by comparing predicted probabilities to the true binary labe"See full answer

Exponent - "This is an Improve a Product question. Let's first go over the Improve a Product formula: Ask clarifying questions Identify users, behaviors, and pain points State product goal Brainstorm small improvements Brainstorm bolder improvements Measure success Summarize Now, let's begin! Ask clarifying questions Before we begin listing off recommendations, it's important you ask questions to ensure you and the interviewer are on the same page"See full answer

Matt M. - "Given the dataset does not contain many labels, it implies we cannot directly use supervised learning. I would ask more about the type of dataset we are given. Is it images, text, etc? This may inform the types of transformations we do the dataset. I can see two approaches to training Given the labels we do have, we can find a method to generate labels for the other unlabeled data. This likely will introduce some error since they may not be true labels, but it at least allows processing the"See full answer

Ali H. - "CIDR (Classless Inter-Domain Routing) -- also known as supernetting -- is a method of assigning Internet Protocol (IP) addresses that improves the efficiency of address distribution and replaces the previous system based on Class A, Class B and Class C networks."See full answer

Kegomoditswe R. - "oracle"See full answer