Philips Interview Experience | Set 7 (Internship)

Round 1: Resume-based shortlisting Phillips Innovation Campus, Bangalore contacted our college to hire Summer Interns for 2 months, starting May 2018. The first round was shortlisting based on resumes. Mostly people who had done projects in Machine Learning and NLP were shortlisted as most of their projects are in this area only. One student whose projects were from the field of augmented virtual reality was also shortlisted. Overall they shortlisted 6 Btech and 5 Mtech students for the next round. I would recommend that if you have done projects in Machine learning then you should highlight those in your resume when applying for Philips. Round 2: Telephonic Interview A panel of 3 people took the telephonic interview. First, they asked about my projects and what all techniques I had used. I had done two projects in ML. One was an article recommendation system and another used Sentiment Analysis to judge a brand's online presence based on reviews on twitter, fb etc.  Then they asked me questions on Machine Learning based on the concepts that had been used in the projects:

1. Explain Matrix Factorization via Singular Value Decomposition
2. Markov Chain Clustering- Algorithm and equations
3. What will you do if data is noisy and incomplete? (Use Expectation Maximisation Algo)
4. EM Algorithm working and equations
5. Questions on cosine similarity and tfidf vectorisation
6. Textblob library: syntax for analysing sentiment of a sentence

Then he asked some general Machine Learning questions :

1.  Which is more important to you– model accuracy, or model performance?
2.  What is the difference between classification and regression and When should you use classification over regression?
3.  Explain how a ROC curve works.
4. What is a confusion matrix? How is it created and what does it depict?

Finally, he asked two programming questions:

1. Find duplicates in an array efficiently: https://www.geeksforgeeks.org/dsa/find-duplicates-in-on-time-and-constant-extra-space/
2. Sliding window maximum problem: https://www.geeksforgeeks.org/dsa/sliding-window-maximum-maximum-of-all-subarrays-of-size-k/

I was able to answer most of the questions up to mark and he seemed pretty impressed. I would recommend having in-depth knowledge of the Machine Learning techniques you have used in your projects and revise basic DSA.  Overall the interview went on for about 25 minutes. They shortlisted 4 Btech and 1 MTech students and I was one of them! Looking forward to working with them :)