Total questions:

10
Answered:

00
Unanswered:

10

Minutes:

20
Seconds:

00

Question:
01
To
05

What is the first step in the data analysis process?

Data collection
Data cleaning
Data visualization
Data modeling

Which of the following is a supervised learning algorithm?

K-Means Clustering
Principal Component Analysis
Decision Trees
Autoencoders

Which Python library is primarily used for data manipulation and analysis?

NumPy
Pandas
Matplotlib
Scikit-learn

In machine learning, what does 'overfitting' refer to?

The model fits the training data too well and performs poorly on new data
The model performs well on new data but poorly on the training data
The model does not have enough training data to learn
The model is too simple and does not capture the complexity of the data

Which metric is used to evaluate classification models?

Mean Squared Error
Confusion Matrix
R-squared
Euclidean Distance

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What is the purpose of using the regularization technique in machine learning models?

To improve accuracy
To prevent underfitting
To reduce variance and prevent overfitting
To simplify data processing

Which of the following is a key advantage of Random Forest over Decision Trees?

It avoids the problem of overfitting
It is easier to interpret
It is faster to train
It requires fewer hyperparameters

What is cross-validation in the context of model evaluation?

Splitting the data into a test set
Testing different algorithms
Resampling the data to assess the model performance
Reducing the number of features

Which of the following techniques can be used for feature selection?

Principal Component Analysis
Random Forest
Lasso Regression
All of the above

Which of these algorithms is used for dimensionality reduction?

K-Means
PCA
Random Forest
Gradient Boosting

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Which of the following is not a type of machine learning?

Supervised Learning
Unsupervised Learning
Reinforcement Learning
Assisted Learning

Which algorithm is best suited for detecting anomalies in data?

K-Means Clustering
Isolation Forest
Naive Bayes
Logistic Regression

In Python, which library would you use to create visualizations?

NumPy
Pandas
Seaborn
Scikit-learn

What is the main goal of clustering in unsupervised learning?

Predict future values
Find relationships between variables
Group similar data points
Improve classification accuracy

Which of the following is an evaluation metric used for regression tasks?

Precision
Recall
Mean Absolute Error
Confusion Matrix

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What is the key difference between bagging and boosting algorithms?

Bagging reduces variance and boosting reduces bias
Bagging is a type of supervised learning and boosting is unsupervised
Bagging uses decision trees and boosting uses SVMs
Bagging combines weak learners and boosting improves weak learners

Which Python function is used to remove missing values in Pandas DataFrame?

dropna()
fillna()
drop()
remove()

Which machine learning algorithm is commonly used for text classification?

K-Means
Naive Bayes
K-Nearest Neighbors
Principal Component Analysis

What is the primary use of the Scikit-learn library in Python?

Data visualization
Data manipulation
Machine learning modeling
Statistical testing

What does the term 'imbalanced data' refer to in a classification problem?

When the number of features is much higher than the number of observations
When one class significantly outnumbers the other class in the dataset
When the data contains missing values
When data contains outliers

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