Un-Answered Questions { AI Machine Learning }
What evaluation approaches would you work to gauge the effectiveness of a machine learning model?
What are the last machine learning papers you've read?
Explain the difference between bias and variance?
Define a fourier transform?
Explain how is knn different from k-means clustering?
How would you use f1 score?
How is bayes' theorem useful in a machine learning context?
Explain the difference between type I and type ii error?
Define kernel svm?
How would you use fl score?
Explain how do classification and regression differ?
Explain how do you ensure you're not overfitting with a model?
What is recall?
Explain how do you handle missing or corrupted data in a dataset?
Explain when should you use classification over regression?
