I don't remember specifics but one question was about pandas, one question about graphs / nodes and one question about lists. I can't remember the last question.
Ai Developer Technology Engineer Interview Questions
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preguntas tecnicas y en ingles
I was asked a wide range of machine learning and AI-related questions, both theoretical and applied. The questions spanned topics such as: Supervised vs unsupervised learning Overfitting and underfitting Evaluation metrics like precision, recall, F1-score, and ROC-AUC Feature engineering and data preprocessing techniques Model selection and hyperparameter tuning Use cases for algorithms like Random Forest, XGBoost, and SVM Basics of deep learning and neural networks I was also asked to solve some practical ML problems live, which involved writing or explaining code, interpreting results, and debugging logic in a collaborative screen-sharing setup. These tasks tested my problem-solving skills, coding proficiency (especially in Python), and ability to think critically under time pressure.
Basically asked me all the details in depth, like the tools I has mentioned in the CV and how I used them. At one point I was basically explaining them each step of deployment for a project I had done.
What projects you have worked on
Why do you want to work here?
They asked if I had any experience with python or worked on any projects with it
Difference between Lists and Arrays, different real world use cases for both.
What is supervised, unsupervised and reinforcement learning?
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