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Feature Engineering Interview Questions and Answers
Home
Questions
Feature Engineering
+1
vote
Q: Can you explain what dimensionality reduction is?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
dimensionality-reduction
+1
vote
Q: What are some good rules of thumb for applying transformations to numeric data?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
transformations
numeric-data
+1
vote
Q: What is the best way to select features in supervised learning problems?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
supervised
learning
problems
+1
vote
Q: How do you handle mixed-type data types in Python?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
mixed-type-data-types
+1
vote
Q: What does it mean to bin numerical data? When should we use this technique?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
bin-numerical-data
+1
vote
Q: Can you give me an example of where feature scaling would be required?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
feature-scaling
+1
vote
Q: What are some methods available for selecting features from a large dataset?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
features
+1
vote
Q: Do all features need to be scaled when using machine learning algorithms?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
machine
learning
algorithms
+1
vote
Q: How can imbalanced datasets affect machine learning models?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
machine-learning-models
+1
vote
Q: What are some ways to deal with sparse data?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
sparse-data
+1
vote
Q: What are some different techniques for dealing with categorical variables?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
techniques-features
+1
vote
Q: If there are two correlated variables, which one should you keep?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
correlated-variables
+1
vote
Q: What’s the difference between feature extraction and feature selection? When should each one be used?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
feature-selection
+1
vote
Q: What can be done if you find that most of your features have no predictive power on your target variable?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
predictive-power
+1
vote
Q: Can you explain how overfitting happens during model training?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
overfitting
model-training
+1
vote
Q: How do you overcome challenges with missing data?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
missing
-data
+1
vote
Q: What are some common ways to gather domain knowledge?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
domain
knowledge
+1
vote
Q: Why is it important to understand your data before starting a project?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
project-data
+1
vote
Q: Can you explain what the term “feature” means in machine learning?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
feature
machine
learning
+1
vote
Q: What is feature engineering?
answered
Apr 4
in
Feature Engineering
by
john ganales
(
13.9k
points)
feature
engineering
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