How to handle missing data in a dataset in Machine Learning?
Explain the difference between machine learning and regression?
Explain the difference between type I and type ii error?
How bayes theorem is useful in a machine learning context?
What is precision and recall?
What is symbolic learning?
What is the difference between type I and type ii error?
Why does overfitting happen?
What is Seq2Seq Tensorflow?
How can you ensure that you are not overfitting with a particular model?
What is decision tree classification?
You are given a data set. The data set has missing values which spread along 1 standard deviation from the median. What percentage of data would remain unaffected? Why ?
Tell me what is a recommendation system?
When should you use classification over regression?
What are neural networks and where do they find their application in ML? Elaborate.