1. Explain Matrix Factorization for the recommendation system. 2. Case study based question. 2. Explain generative adversarial networks. 3. Loss function of GAN 4. Coding question, solve n stairs problem. every time we can take step 1 ot step 2. print max possibles ways. use either dynamic or recursive approach.
Qu'est-ce que vous referiez différement dans un poste précédent ? Mon client n'a pas confiance dans le modèle de Machine Learning proposé, que faire ?
Tipical HR interview, what do you know about Glovo etc etc
SQL, machine learning related questions
Focus on my projects, AWS knowledge, data science and ML basics
One of the questions at the panel interview focused on how to handle high-cardinality categorical variables in a model, especially when a naive approach could introduce noise or performance issues. The discussion was very practical and centered on trade-offs rather than theoretical tricks.
For a regression, under which assumptions MSE and log-likelihood are proportional?
Mathematical Modeling questions
1. Case studies related to the main skills they looking for as job descriptions. 2. If you have really done the work mentioned on your resume just dive in-depth into it. 3. Be confident, a professional look are important
Asked on experience with data science technologies - Spark, Python, R..
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