Data Modelling

What is a model in the context of AI?

• "A representation of a process"
• "A type of computer hardware"
• "A programming language"
• "A dataset"

Answer explanation

"In AI a model is a mathematical representation used to predict outcomes based on input data."

What does 'data preprocessing' involve?

• "Collecting raw data"
• "Cleaning and transforming data"
• "Analyzing data trends"
• "Visualizing data"

Answer explanation

"Data preprocessing prepares raw data for modeling by cleaning and transforming it to make it suitable for analysis."

What is a feature in a dataset?

• "A label for data"
• "An attribute or characteristic"
• "A model parameter"
• "A type of algorithm"

Answer explanation

"Features are the individual measurable properties or characteristics used in modeling to make predictions."

What does 'training data' refer to?

• "Data used to test the model"
• "Data used to improve the model"
• "Data used to train the model"
• "Data collected for future use"

Answer explanation

"Training data is the dataset used to teach the model how to make predictions or decisions."

What is the purpose of a model's accuracy?

• "To determine the amount of data"
• "To measure how well the model performs"
• "To select features"
• "To preprocess data"

Answer explanation

"Accuracy measures the proportion of correct predictions made by the model compared to the total predictions."

What does 'overfitting' mean in modeling?

• "Model performs well on training data but poorly on new data"
• "Model is too simple"
• "Model runs too slowly"
• "Model has too many features"

Answer explanation

"Overfitting occurs when a model learns the noise in the training data failing to generalize to new data."

What is the role of a 'label' in supervised learning?

• "An identifier for data"
• "The expected output for a given input"
• "A measure of performance"
• "A feature in the dataset"

Answer explanation

"In supervised learning labels are the outputs associated with input data used to train the model."

What is a 'classification model'?

• "A model that predicts numerical values"
• "A model that categorizes data"
• "A model that cleans data"
• "A model that collects data"

Answer explanation

"A classification model assigns input data into predefined categories based on learned patterns."

What does 'validation data' help with?

• "Training the model"
• "Testing final performance"
• "Evaluating model performance during training"
• "Collecting more data"

Answer explanation

"Validation data is used to fine-tune the model during training and assess its performance on unseen data."

What is the difference between supervised and unsupervised learning?

• "Supervised uses labels; unsupervised does not"
• "Both use labeled data"
• "Both use unlabeled data"
• "Unsupervised is faster"

Answer explanation

"Supervised learning uses labeled data to train the model while unsupervised learning finds patterns in unlabeled data."