The capstone project is the final step in the learning journey. It allows students to apply all concepts learned throughout the course.
The first step is selecting a problem statement. This could be predicting house prices, detecting spam, or building a recommendation system.
Next, students collect and prepare data. This includes cleaning and preprocessing the dataset.
Then, students select a suitable model and train it using the data. Model selection depends on the problem type.
After training, the model is evaluated using appropriate metrics. This ensures that the model performs well.
Finally, students present their results, explaining their approach, challenges, and outcomes.
The capstone project helps students gain hands-on experience and builds confidence in applying machine learning concepts in real-world scenarios.
