(Mostly) whenever we see kernel visualizations online (or some other reference) we are actually seeing:

The activations for class A, B and C before softmax were 10,8 and 3. The different in softmax values for class A and class B would be :

The new dataset you have just scraped seems to exhibit lots of missing values. What action will help you minimizing that problem?

Which of the following methods can use either as an unsupervised learning or as a dimensionality reduction technique?

What is the main motivation for using activation functions in ANN?

Which loss function would fit best in a categorical (discrete) supervised learning ?

Which ofthe following boosting algorithms implements regularization that helps in reducing overfitting?

Logistic regression can be used with which of the following types of dependent variables?

Which of the following statements is/are correct about unsupervised machine learning?

Which of the following is NOT an advantage of simulation modelling and analysis?

Which SimPy function calls is/are used in marking a thread as runnable when it is first created?