Welcome to your AI Engineer
AI engineer
1. Which algorithm is used to minimize the cost function in neural networks?
K-Means
Naïve Bayes
Random Forest
Gradient Descent
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AI engineer
2. What is the main purpose of an activation function in a neural network?
Increase training speed
Reduce overfitting
Normalize input data
Introduce non-linearity
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AI engineer
3. Which of the following is a supervised learning algorithm?
PCA
K-Means
Linear Regression
DBSCAN
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AI engineer
What is the function of a loss function in machine learning?
It measures model error
It stores weights
It normalizes inputs
It visualizes data
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AI engineer
In deep learning, what does ReLU stand for?
Random Linear Unit
Rectified Linear Unit
Recurrent Linear Unit
Regularized Linear Update
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AI engineer
Which layer in a neural network is responsible for feature extraction?
Hidden layers
Normalization layer
Output layer
Input layer
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AI engineer
What is overfitting in AI models?
Model performs poorly on training data
Model stops training early
Model performs well on test data only
Model performs well on training but poorly on test data
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AI engineer
Which of these is an example of an unsupervised learning problem?
Clustering Customer Data
Sentiment Analysis
Stock Price Prediction
Spam Detection
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AI engineer
Which of the following metrics is used for classification problems?
Accuracy
R² Score
Mean Absolute Error
Mean Squared Error
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AI engineer
What does CNN stand for in deep learning?
Central Neural Network
Complex Neural Node
Convolutional Neural Network
Clustered Neural Network
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AI engineer
Which algorithm is used for dimensionality reduction?
PCA
Logistic Regression
KNN
Decision Tree
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AI engineer
What does CNN stand for in deep learning?
Complex Neural Node
Central Neural Network
Convolutional Neural Network
Clustered Neural Network
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AI engineer
What does dropout do in neural networks?
Decreases overfitting by randomly disabling neurons
Removes features permanently
Normalizes data
Increases learning rate
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AI engineer
What is a hyperparameter?
A learned weight
A parameter set before training
A loss value
A model output
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AI engineer
Which type of neural network is best suited for sequential data?
GAN
SVM
CNN
RNN
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AI engineer
GAN stands for what?
Generative Adversarial Network
General Adversarial Network
Graph Attention Network
Gradient Applied Network
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AI engineer
What is backpropagation used for?
Cleaning data
Storing gradients
Updating model parameters
Initializing weights
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AI engineer
Which loss function is commonly used for classification?
Cross-Entropy Loss
Mean Squared Error
Hinge Loss
Smooth L1 Loss
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AI engineer
What is the role of the softmax function?
Converts outputs to probabilities
Normalizes inputs
Reduces bias
Increases learning rate
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AI engineer
Which library is most commonly used for deep learning in Python?
Pandas
TensorFlow
Matplotlib
NumPy
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AI engineer
What is a confusion matrix used for?
Weight initialization
Feature selection
Displaying correlations
Evaluating classification performance
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AI engineer
In NLP, what does tokenization mean?
Splitting text into words or subwords
Encoding data
Compressing text
Removing stopwords
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AI engineer
Which optimizer adapts learning rate for each parameter?
SGD
Adam
RMSprop
MiniBatch
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AI engineer
What is the purpose of regularization?
Increase model complexity
Prevent overfitting
Speed up training
Normalize data
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AI engineer
In reinforcement learning, what is a policy?
A mapping from states to actions
A discount factor
An environment
A reward function
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