Loss Functions in TensorFlow
The loss metric is very important for neural networks. As all machine learning models are one optimization problem or another, the loss is the objective function to minimize. In neural networks, the optimization is done with gradient descent and backpropagation. But what are loss functions, and how are they affecting your neural networks?
In this post, you will learn what loss functions are and delve into some commonly used loss functions and how you can apply them to your neural networks.
After reading this article, you will learn:
- What are loss functions, and how they are different from metrics
- Common loss functions for regression and classification problems
- How to use loss functions in your TensorFlow model
Let’s get started!