Data Science Advanced Quiz 7 > Data AI Revolution

Test your expertise in data science with this advanced-level quiz! Covering key concepts like machine learning algorithms, data preprocessing, model evaluation, feature engineering, and deep learning, this quiz challenges your knowledge across statistics, programming,

1 / 10

In Bayesian statistics, what is the posterior probability?

The probability of observing the data given the parameters

The probability of the parameters given the observed data

The prior probability of the parameters

The likelihood of the model

2 / 10

Which deep learning architecture is best suited for sequential data like time series?

Convolutional Neural Networks (CNN)

Recurrent Neural Networks (RNN)

Random Forest

Naive Bayes Classifier

3 / 10

Which of the following is a method of clustering where each data point belongs to multiple clusters?

K-Means

Hierarchical Clustering

Fuzzy C-Means

DBSCAN

4 / 10

In reinforcement learning, what is the ‘exploration vs exploitation’ trade-off?

Choosing between maximizing the current reward or learning from new actions

Choosing between two equally probable actions

Minimizing loss while maximizing rewards

Reducing the error while increasing reward rate

5 / 10

Which of the following techniques can help prevent overfitting in deep learning models?

Learning rate

Dropout

Batch Normalization

Min-max scaling

6 / 10

In natural language processing (NLP), what does TF-IDF stand for?

Term Frequency - Inverse Document Frequency

Term Frequency - Indexed Data Frequency

Text Frequency - Inverse Document Format

Text Feature - Indexed Data Format

7 / 10

Which gradient descent algorithm updates the weights after every training example?

Batch Gradient Descent

Stochastic Gradient Descent

Mini-batch Gradient Descent

Adaptive Gradient Descent

8 / 10

Which of the following can be used for feature selection?

Recursive Feature Elimination (RFE)

K-Means Clustering

Support Vector Machines

Principal Component Analysis

9 / 10

What does the ROC curve represent?

Trade-off between precision and recall

Relationship between true positive rate and false positive rate

Accuracy of the model

The probability distribution of the classes

10 / 10

Which of the following is an unsupervised learning algorithm?

Logistic Regression

Decision Tree

K-Means

Naive Bayes

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Data Science Advanced Quiz 7

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