Internadda
20:00

1Which type of machine learning uses labeled data to train models?

Unsupervised Learning
Supervised Learning
Reinforcement Learning
Semi-supervised Learning

2What is the primary goal of a classification algorithm?

To assign data points to predefined categories.
To predict a continuous numerical value.
To find hidden structures or groups in data.
To learn through trial and error based on rewards.

3Which algorithm is commonly used for clustering (grouping similar data points)?

Linear Regression
Support Vector Machine (SVM)
Decision Tree
K-Means

4In Natural Language Processing (NLP), what does 'tokenization' mean?

Translating text from one language to another.
Summarizing a long piece of text.
Breaking down text into smaller units like words or sentences.
Identifying the sentiment (positive/negative) of text.

5What is 'Overfitting' in the context of machine learning models?

The model is too simple and cannot capture the underlying patterns.
The model learns the training data too well, including noise, and performs poorly on new data.
The model fails to converge during training.
The dataset used for training is too small.

6Which Python library is fundamental for numerical computing and underlies many ML libraries like TensorFlow and PyTorch?

NumPy
Pandas
Matplotlib
Scikit-learn

7What does a 'Confusion Matrix' help visualize in a classification problem?

The correlation between different features.
The distribution of data points in clusters.
The feature importance scores.
The performance of the model in terms of true positives, true negatives, false positives, and false negatives.

8Which activation function is commonly used in the output layer of a binary classification neural network?

ReLU (Rectified Linear Unit)
Tanh (Hyperbolic Tangent)
Sigmoid
Linear

9What is the primary advantage of using a 'Validation Set' during model training?

To increase the training speed.
To tune hyperparameters and prevent overfitting on the test set.
To visualize the final results.
To perform feature engineering.

10Gradient Descent is an algorithm commonly used for what purpose in machine learning?

Optimizing the model's parameters by minimizing a loss function.
Splitting the data into training and testing sets.
Selecting the most important features.
Evaluating the model's accuracy.

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