Asked about my background. Asked about which potential projects I was interested in from the list. Asked some basic questions on ML fundamentals (i.e. How are bias and variance related to over/underfitting) and a few more in-depth questions about specific algorithms (difference between GRU and LSTM).
Explain your current role Questions related to experience and current role.
How do you learn? What mediums do you use to learn? What is challenging something you have taught yourself recently? How have you overcome something you were stuck on?
1. Questions regarding experience using STAR. 2. Metrics in imbalance datasets
How would you implement multi-arm bandits in the context of hotel recommendations?
1. Organizzare il codice in classi seguendo principi di software design (SOLID etc) 3. Qual è il tuo modello di deep learning preferito e perché, come lo metteresti in prod 4. Cosa cambieresti del processo nella tua azienda dal punto di vista del dato
Stuff about Spark, Kinesis, SQL, Tensorflow, PyTorch
Take us through a project you've worked on.
1. Custom named entity recognition model
Q: How do you evaluate the performance a classifier?
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