Train and test a machine learning model to solve a real-world problem.
Describe the stages of the AI project lifecycle
Use a machine learning tool to import data and train a model
Test and examine the accuracy of an ML model
AI project lifecycle, data cleaning, machine learning model, class, label, training, testing, accuracy, confidence score, confidence threshold
Order the stages of the AI project lifecycle
User-focused approach
Stage 1: Defining the problem
Stage 2: Preparing the data
Stage 3: Training the model
Stage 4: Testing the model
Reporting on the accuracy of a model
