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Ml Engineer Interview Questions
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Questions on Linear regression and model evaluation
How do transformers work, what is the main drawback.
how do you make a SLM to be good at reasoning
They asked me on the nlp side Skipgram and cbow
conflict between you and your professor
how to make recommendation system
To estimate future number of downloads based on graphs
1. Explain the concept of overfitting in machine learning and how it can be addressed. 2. Discuss the differences between supervised and unsupervised learning algorithms. 3. How would you handle imbalanced datasets in machine learning projects? 4. Describe the process of feature selection and its importance in model development. 5. Have you worked with any deep learning frameworks? If so, which ones and what was your experience like? 6. How do you evaluate the performance of a machine learning model? 7. Can you explain the bias-variance tradeoff and its significance in model training? 8. Discuss regularization techniques in machine learning and when they should be used. 9. Have you implemented any natural language processing (NLP) algorithms? If yes, explain the approach and challenges faced. 10. How would you approach a project with limited labeled data for training a machine learning model?
1.explan transformer. 2.write the confusion matrix code
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