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I applied via Campus Placement and was interviewed before Jul 2021. There were 2 interview rounds.
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They asked some technical interview questions
Was good and you get questions from various topics.
Apti
Basics of cs
Per question time good amoubnt of questions
I was interviewed before Aug 2016.
I was interviewed before Feb 2016.
I was interviewed in Apr 2017.
I am a software developer with a passion for coding and problem-solving. My family is supportive and has always encouraged my career in tech.
Experienced software developer
Passionate about coding and problem-solving
Supportive family that encourages my career in tech
Yes, I can remove all the pcs from the lab and keep them in another lab right now.
Ensure all the necessary equipment and tools are available for the move
Coordinate with the lab staff to ensure a smooth transition
Label and document each PC for easy identification and setup in the new lab
Ensure proper packaging and handling to prevent any damage during the move
Fibonacci series is a sequence of numbers where each number is the sum of the two preceding ones.
The first two numbers of the series are always 0 and 1
The next number is the sum of the previous two numbers
The series goes on infinitely: 0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, ...
Pseudo code: 1. Initialize variables a=0, b=1, c=0 2. Print a and b 3. Repeat steps 4-6 until desired number of terms 4. c=a+b 5. Pr
Algorithm for matrix multiplication
Create a result matrix with dimensions of the two input matrices
Iterate through each row and column of the result matrix
For each element in the result matrix, multiply corresponding row in first matrix with corresponding column in second matrix
Add the products obtained in the previous step to get the final value for the element
I worked on a project that involved sentiment analysis of customer reviews using Naive Bayes algorithm.
The project involved collecting customer reviews from various sources.
Preprocessing the data by removing stop words, stemming, and tokenizing.
Used Naive Bayes algorithm for sentiment analysis.
The algorithm was chosen because of its simplicity and effectiveness in text classification tasks.
The accuracy of the model was
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