WorksheetsAI and ML Introduction
Total questions: 20
Worksheet time: 3mins
Which of the following statement is true about AI and ML
AI is a subset of ML
ML is a subset of DL
AI is a subset of DL
ML is a subset of AI
Identify the AI powered personal assistant developed by Amazon
Below is the deep learning model used generate new paintings
CNN
GAN
ANN
RNN
Machine Learning happens through
Data
Algorithms
Reading
Classification
Validation is a part of
Testing
Training
Learning
data cleaning
This is the first phase in machine learning life cycle
Training
Data collection
Algorithm selection
Visualization
Which of these is not an AI technology
Face Recognition
Robotics
Animation
Speech Recognition
The ability of computers to understand images and video
Robotics
Computer vision
NLP
Image processing
Which of the following is a common application of computer vision?
Speech recognition
Image classification
Data mining
Natural language processing
What is the primary purpose of data preprocessing in machine learning?
To visualize data
To collect data
To improve model accuracy
To select algorithms
Which algorithm is primarily used for supervised learning?
Principal component analysis
Generative adversarial networks
Decision trees
K-means clustering
What is the main difference between supervised and unsupervised learning?
Supervised learning uses labeled data
Unsupervised learning uses labeled data
Unsupervised learning is more accurate
Supervised learning is faster
Which of the following is a technique used for feature selection?
Cross-validation
Normalization
Regularization
Clustering
What is the purpose of a confusion matrix in machine learning?
To visualize data
To evaluate model performance
To preprocess data
To select features
What is the role of hyperparameters in machine learning models?
To preprocess data
To evaluate model performance
To control the learning process
To define the model architecture
Which of the following is a common method for model evaluation?
Cross-validation
Data augmentation
Feature extraction
Data normalization
What is the main advantage of using ensemble methods in machine learning?
They reduce overfitting
They increase model complexity
They require less data
They simplify the model
What is the purpose of feature engineering in machine learning?
To improve model performance
To visualize data
To collect more data
To select algorithms
Which of the following is a common technique for handling missing data?
Clustering
Normalization
Imputation
Data augmentation
What is the main goal of unsupervised learning?
To predict outcomes based on labeled data
To reduce dimensionality of data
To find hidden patterns in unlabeled data
To classify data into predefined categories
