Top 50 data Science Interview Questions | Data Science Aptitude Questions Answers

How to ensure we are not over fitting the model?

Keep the attributes/Columns which are really important
Use K-Fold cross-validation techniques Make use of drop-put in case of neural network
How the root node is predicted in Decision Tree Algorithm?
Mathematical Formula “Entropy” is utilized for predicting the root node of the tree.

What are the different Backend Process available in Keras?

TensorFlow
Theano
CNTK
Q126. Name Few Deep Learning
Algorithm
TensorFlow
Theano
Lasagne
mxnet
blocks
Keras
CNTK
TFLearn

How to split the data with equal set of classes in both training and testing data?

Using Stratified Shuffle package

What do you mean by Ensemble Model? When to use?

Ensemble Model is a combination of Different Models to predict correctly and with good accuracy.
Ensemble learning is used when you build component classifiers that are more accurate and independent from each other.

When will you use SVM and when to use Random Forest?

SVM can be used if the data is outlier free whereas Naïve Bayes can be used even if it has outliers (since it has a built-in package to take care).
SVM suits best for Text Classification Model and Random Forest suits for Binomial/Multinomial Classification Problem.
Random Forest takes care of overfitting problem with the help of tree pruning