Deep Learning - Crash Course 2023 - Learning Algorithms and Model Performance

The video tutorial covers key concepts in deep learning, focusing on learning algorithms and model performance measures. It explains the role of loss functions and parameter adjustments in optimizing models. Various learning algorithms like gradient descent and its variants are discussed. The application of these algorithms in neural networks, particularly in facial recognition, is demonstrated. The video concludes with the evaluation process of neural networks using test data to measure efficiency.

Explain the process of adjusting parameters in a learning algorithm.

What is the purpose of a learning algorithm in machine learning?

What are some examples of learning algorithms mentioned in the text?

How do you test the performance of a trained neural network?

Describe the evaluation process of a neural network after training.