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Black Box Corporation
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I applied via LinkedIn and was interviewed before Apr 2022. There were 4 interview rounds.
Top trending discussions
I applied via Walk-in and was interviewed before Feb 2022. There were 3 interview rounds.
All Logical questions plus coding
I applied via Campus Placement and was interviewed before Sep 2020. There were 3 interview rounds.
Python code to find the root of a number
Use the math module to access the sqrt() function
Use the ** operator to raise the number to the power of 1/n
Handle negative numbers by converting them to complex numbers
I appeared for an interview before Mar 2024, where I was asked the following questions.
Some mcq questions and coding question. Both where easy to medium level. Prepare combination/permutation/Time complexity etc
A question related to Binary search and some other follow ups.
I switched jobs to pursue new challenges and opportunities for growth.
Seeking new challenges and opportunities for personal and professional growth
Desire for a change in work environment or company culture
Interest in exploring different industries or roles
Wanted to learn new skills or gain more experience
Looking for better work-life balance or compensation
Example: I wanted to switch to a company that values innovation ...
I am comfortable with shift timings and can adapt to different schedules.
I have experience working various shifts in previous roles
I am flexible and can adjust my schedule as needed
I understand the importance of being reliable and punctual in a shift-based job
General Aptitude( Probability dominats) and objective coding
Moderate levels coding questions Refer hacker rank
I applied via Campus Placement and was interviewed before Nov 2022. There were 4 interview rounds.
Probability, coding, coordinate geometry , debugging, predict the output
1 hour test 3 questions , one was on numbers I don't remember much , random people get selected in 3rd round in campus placements
I applied via Referral and was interviewed in Jul 2021. There were 4 interview rounds.
C is the regularization parameter while gamma controls the shape of the decision boundary in SVM.
C controls the trade-off between achieving a low training error and a low testing error.
A smaller C value creates a wider margin and allows more misclassifications.
Gamma controls the shape of the decision boundary and the influence of each training example.
A smaller gamma value creates a smoother decision boundary while a l...
based on 1 interview
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