Ho presentato la mia candidatura tramite l'università. La procedura ha richiesto un giorno. Ho sostenuto un colloquio presso Celebal Technologies (Jaipur, Rajasthan) nel mese di set 2022
Colloquio
Round 1: Technical interview where one Python coding question was asked followed by Python basics and Machine Learning/Deep Learning basics were asked. The concepts were fundamental level but the depth was significant. Python question was easy to medium level and also they will also ask about your project given in the resume and reasoning for using the particular ML model. Round 2: HR interview. Just a 5-10 minutes interview where asked questions like co-curricular activity and preferred location.
Domande di colloquio [6]
Domanda 1
Examples of ensemble classification technique in ML and explain it.
Question related to my project given in my resume: Why did you used LSTM model rather than an Auto-regressive model for time-series forecasting of stock-prices?
Ho presentato la mia candidatura tramite l'università. La procedura ha richiesto 2 settimane. Ho sostenuto un colloquio presso Celebal Technologies nel mese di set 2025
Colloquio
Note: This was an on-campus hiring.
1. Kaggle Competition for a given problem statement (university wise)
2. Online Online Assessment round consisting of aptitude and Data Structures and Algorithms
3. 2 Technical Interview rounds
4. HR round
Ho presentato la mia candidatura tramite l'università. Ho sostenuto un colloquio presso Celebal Technologies (Jaipur, Rajasthan) nel mese di ago 2022
Colloquio
The interview lasted for about 1 hr 15 min. Easy to medium level i can say. You can easily clear it if you have your basic concepts clear. Basic understanding of classical ML, Python, NLP and SQL are what they look for.
Domande di colloquio [1]
Domanda 1
Q1. Model evaluation Techniques Q2. Lambda function Q3. Seaborn vs matplotlib Q4. About the libraries used in your project Q5. Decision Tree, Random Forest Q6. Overfitting underfitting and ways to handle them Q7. L1 L2 regularization