- Loss Functions
- TensorFlow Training Classes Python API
- Gradient Descent Optimization & Challenges
- Objective vs. Cost vs. Loss vs. Error Function
- H2O Driverless AI - Intro + Interactive Hands-on Lab - Video
There are many options for optimizer in Tensorflow. Optimizers are the tool to minimise loss between prediction and real value. There are many different weights a model could learn, and brute-force testing every one would take forever. Instead, an optimizer is chosen which evaluates the loss value, and smartly updates the weights. Click here For a list of Keras optimizer functions. Optimizer is one of the two parameters required to compile a model...
Genetic Algorithm Optimization