Machine Learning Mcq

Machine Learning MCQ: Test Your Knowledge!

 

 

What is BERT in the context of NLP?
A type of chatbot
A pre-trained language model
A programming language
A data format for text
What is the primary function of BigQuery ML in machine learning?
To create small datasets
To train models using SQL in BigQuery
To visualize machine learning results
To deploy models to production
What is a typical output of a clustering algorithm?
Groups of similar data points
Predictions of future events
Reduced data noise
A visualization of the dataset
What is hyperparameter tuning in machine learning?
The process of training a model
The process of optimizing model architecture parameters
The process of cleaning data
The process of feature selection
What is the main purpose of hyperparameter tuning in machine learning?
To increase the size of the training dataset
To optimize model performance
To reduce the number of features
To eliminate overfitting completely
What are embeddings in NLP?
A type of punctuation
Vector representations of words or phrases
A method of text encryption
A form of data compression
What is feature engineering?
The process of selecting and transforming variables for a model
A technique for clustering data
A method for generating new data
A tool for data visualization
What is the primary difference between generative AI and traditional machine learning?
Generative AI can only work with images
Traditional ML is always more accurate
Generative AI can create new content, while traditional ML typically makes predictions or classifications
There is no difference between them
What is the main purpose of conversation buffer memory in LangChain?
To increase conversation speed
To store and manage conversation history
To encrypt conversation data
To compress conversation logs
What is the purpose of the Wasserstein distance in machine learning?
To perform classification
To measure the distance between probability distributions
To reduce dimensionality
To generate synthetic data
Machine learning is a subset of deep learning.
False
True
Partially true
Depends on the context
What is class imbalance in machine learning?
When one class has significantly more samples than others
When all classes have equal samples
When the model performs equally on all classes
When the dataset is too small
What is the primary advantage of using deep learning for chatbots?
They never make mistakes
They can understand and generate more natural language
They don't require any training data
They are always faster than rule-based chatbots
Which step in a typical machine learning process involves testing the solution on the test data?
Data collection
Model training
Model validation
Model testing
What is the main idea behind the YOLO (You Only Look Once) algorithm?
It's a type of RNN
It's a real-time object detection system
It's a clustering algorithm
It's a technique for data augmentation
What is supervised learning used for?
Learning from labeled data to make predictions
Learning from unlabeled data
Clustering similar data points
Generating new data samples
How does machine learning handle large datasets?
By using techniques like distributed computing and parallel processing
By ignoring the large data size
By reducing the dataset size manually
By increasing the noise in the dataset
How is an artificial neural network related to machine learning?
It is a type of machine learning algorithm
It is unrelated to machine learning
It is a data preprocessing tool
It is only used in AI
What is a real-world application of clustering?
Customer segmentation for targeted marketing
Predicting stock prices
Classifying email as spam or not spam
Reducing data dimensionality
What type of deep learning algorithms are typically used by generative AI?
Convolutional Neural Networks
Recurrent Neural Networks
Generative Adversarial Networks
Decision Trees
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