The interviewer was unprepared, disorganized, and uninterested. They asked vague, irrelevant questions and barely listened to responses. No clear structure, no enthusiasm, and no respect for time. The process felt rushed and pointless, leaving a negative impression about the company.
Hardly any questions about me, except for the self introduction.
A Python coding question was given to be completed within 45 minutes.
A start-up owner is looking to meet new investors to get some funds for the company. Each investor has a tight schedule that the owner has to respect. Given the schedules of the days investors are available, determine how many meetings the owner can schedule. Note that the owner can only have one meeting per day. The schedules consist of two integer arrays: firstDay, and lastDay, aligned by index. Each element in the array firstDay represents the first day an investor is available, and each element in lastDay represents the last day an investor is available, both inclusive. Example: firstDay = [1,2,3,3,3] lastDay= [2,2,3,4,4] • There are 5 investors [I-0, 1-1, I-2, I-3, 1-4] • The investor I-0 is available from day 1 to day 2 inclusive [1, 2] • The investor I-1 is available in day 2 only [2, 2]. The investor 1-2 is available in day 3 only [3, 3] • The investors I-3 and I-4 are available from day 3 to day 4 only [3, 4] • The owner can only meet 4 investors out of 5: I-0 in day 1, 1-1 in day 2, 1-2 in day 3 and I-3 in day 4. Function Description Complete the function countMeetings in the editor below. countMeetings has the following parameters: int firstDayIn]: firstDaytil is the first day the ith investor is available to meet. int lastDayIn]: lastDayli] is the last day the ith investor is available to meet. Returns: int: the maximum number of meetings possible Constraints • 1 ≤ n ≤ 105 • 1 s firstDayli], lastDayli] ≤ 105 (where 0 ≤ i < n) • firstDayli] ≤ lastDayli] (where 0 ≤ i < n)
model Fraud Detection with their dataset
Describe diffusion model and their application
There were 2 business cases related to their basic problems like hotel recommendation. You need to start describing the solution, taking into account the lack of users at the beginning, and how the solution will be improved in the future.
Did you have any experience with deployment or operationalization of models? What are the things you look into before deploying the model?
Walk me through your ML experience. Why Compass?
You have a partially observable environment with evolving dynamics (non-stationary transition and reward distributions). Logged data comes from multiple behavior policies. How would you estimate the expected return of a new policy and safely improve it, without deploying it, while accounting for uncertainty in both the dynamics and the behavior policies?
Viewing 41 - 50 interview questions