AI Project cycle Flashcards
What is the first stage of the AI project cycle?
Problem Definition
True or False: Data Collection is a crucial step in the AI project cycle.
True
Fill in the blank: The process of preparing data for analysis is known as __________.
Data Preprocessing
What stage follows Data Preprocessing in the AI project cycle?
Model Development
Which of the following is NOT a common type of AI model? (a) Decision Trees (b) Neural Networks (c) Linear Regression (d) Data Collection
d) Data Collection
What is the purpose of model evaluation in the AI project cycle?
To assess the performance of the AI model using various metrics.
True or False: Deployment is the final step in the AI project cycle.
True
What does model tuning refer to in the AI project cycle?
Adjusting model parameters to improve performance.
Which phase involves gathering relevant data to solve the problem?
Data Collection
Fill in the blank: The process of using a model in a real-world setting is called __________.
Deployment
What is the primary goal of the AI project cycle?
To develop and implement effective AI solutions.
True or False: Continuous monitoring is unnecessary after deployment.
False
What is the significance of feedback loops in the AI project cycle?
They allow for iterative improvements based on model performance.
What does the term ‘overfitting’ mean in the context of AI models?
When a model learns the training data too well, failing to generalize to new data.
What is one common metric used for model evaluation?
Accuracy
Fill in the blank: The stage where data is transformed and cleaned is known as __________.
Data Preprocessing
What role does feature selection play in the AI project cycle?
It helps in identifying the most relevant data attributes for model training.
True or False: The AI project cycle is a linear process.
False
What is one challenge faced during the Data Collection phase?
Ensuring data quality and relevance.
Which of the following is a common AI model evaluation technique? (a) Cross-validation (b) Data Collection (c) Model Deployment (d) Feature Extraction
a) Cross-validation
What is the purpose of data augmentation in AI projects?
To artificially increase the size of the training dataset.
What is the last step in the AI project cycle?
Monitoring and Maintenance
Fill in the blank: The stage of the AI project cycle where the project is conceptualized is called __________.
Problem Definition
True or False: AI models do not require retraining once deployed.
False
