Probabilistic Deep Learning

3 Principles of curve fitting

This chapter covers

• How to fit a parametric model
• What a loss function is and how to use it
• Linear regression, the mother of all neural networks
• Gradient descent as a tool to optimize a loss function
• Implementing gradient descent with different frameworks

DL models became famous because they outperformed traditional machine learning (ML) methods in a broad variety of relevant tasks such as computer vision and natural language processing. From the previous chapter, you already know that a critical success factor of DL models is their deep hierarchical architecture. DL models have millions of tunable parameters, ...