# Samsung R&D Interview Experience | Set 37 (For developer profile)

Samsung R&D Bengaluru, visited our campus for full time recruitment. There were 5 rounds in total.

1) Online coding round

2) GD

3) Technical round 1

4) Technical round 2

5) HR

Round 1: Online Coding round

This was a 3 hours coding round in which we had to code 1 problem having 10 test cases. Only those students were selected for the next round who passed all the test cases.
Note- You can compile your code as many number of times as you want, but a maximum of 5 submissions were allowed to test on the given test cases.

Here is the question:-

Mr. Kim has to deliver refrigerators to N customers. From the office, he is going to visit all the customers and then return to his home. Each location of the office, his home, and the customers is given in the form of integer coordinates (x,y) (-1<x<101, -1<y<101) . The distance between two arbitrary locations (x1, y1) and (x2, y2) is computed by |x1-x2| + |y1-y2|, where |x| denotes the absolute value of x; for instance, |3|=|-3|=3. The locations of the office, his home, and the customers are all distinct. You should plan an optimal way to visit all the N customers and return to his among all the possibilities.

You are given the locations of the office, Mr. Kim’s home, and the customers; the number of the customers is in the range of 5 to 10. Write a program that, starting at the office, finds a (the) shortest path visiting all the customers and returning to his home. Your program only have to report the distance of a (the) shortest path.

You don’t have to solve this problem efficiently. You could find an answer by looking up all the possible ways. If you can look up all the possibilities well, you will get a perfect score.

[Constraints]

4<N<11. Each location (x,y) is in a bounded grid, -1<x<101, -1<y<101, and x, y are integers.

[Input]

You are given 10 test cases. Each test case consists of two lines; the first line has N, the number of the customers, and the following line enumerates the locations of the office, Mr. Kim’s home, and the customers in sequence. Each location consists of the coordinates (x,y), which is reprensented by ‘x y’.

[Output]

Output the 10 answers in 10 lines. Each line outputs the distance of a (the) shortest path. Each line looks like ‘#x answer’ where x is the index of a test case. ‘#x’ and ‘answer’ are separated by a space.

[I/O Example]

Input (20 lines in total. In the first test case, the locations of the office and the home are (0, 0) and (100, 100) respectively, and the locations of the customers are (70, 40), (30, 10), (10, 5), (90, 70), (50, 20).)

5 (Starting test case #1)

0 0 100 100 70 40 30 10 10 5 90 70 50 20

6 (Starting test case #2)

88 81 85 80 19 22 31 15 27 29 30 10 20 26 5 14

Output (10 lines in total)

#1 200

#2 304

HINT:- Use BackTracking

2) GD

We were given a problem in ML.

Problem was to predict the no. of cycles would be required by a cycle renting company(like OLA ) at a given point of time. Given previous data with various features of service  like time of service, date , city name, humidity , temp , etc predict no of cycles required in that city at give time.

We discussed about linear regression , feature reduction, naive bayes prediction , classifiers , feature selection techniques.

I thought the idea was to keep solution as simple as possible initially . For such task  linear regression would be good , Jumping  to ANN would not help in front of them.

We also discussed about how to  store this data on disk or hdfs etc.

For storing data , we discussed about storing in SQL or Nosql databases. Advantages and disadvantages. How we will create indexes for fast access.  It lasted for 40 mins.

6 were shortlisted out of 9.

3) Technical round -1

1. Introduce yourself
2. Area of interest.
3. Linear regression, write code for gradient descent, Stochastic gradient descent, feature reduction and selection techniques, information gain , decision trees, random forest .
4. Then he asked question about my research posters from my CV.
5. He asked  me to create a question answering system . where we discussed about document  indexing , merging posting lists , pos tagging , named entity recognition ,stemming ,stop words removal etc (Basically he was testing me in NLP , IR , ML ), we discussed this for 20-25 minutes . Interviewer was very helpful.
6. After this, we discussed about deep learning approaches for question answering system.
7. Questions on tensorflow , Numpy , diff between python and C++ .

It lasted for about 1 hr.

4) Technical round -2

1. Various classifiers like SVM (in depth ) , decision trees vs random forest , Bagging boosting , etc.
2. Discussion about my internship project on image classification.
3. Create a system to convert speech to handwritten documents. We discussed about how to recognise one’s handwriting , language modelling ,  spelling correction , feedback from user, etc
4. What new can I see in mobile security using ML ?
5. Real life applications of all my projects written in CV.
6. And then final discussion about my favourite project among those.

It lasted for about 1 hr.

5) HR round
In both technical interviews they asked me from my CV . so Defend your CV well.

From interviews I learned , Given a problem one should approach step wise to bring solution . Like given a ML problem , one should not straight away jump to ANN and RNN , etc . Initially give them a simple solution of a problem (like a brute force) and then build up your discussion with further improving it. It will reflect your depth in subjects to interviewer.

If you are stuck something ask interviewer for help .

Best of luck

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