We will view a summary of the different networks as we create them by using the summary
method on the model. This will help us better understand the structure of the model.
Instructor: [00:01] You can print a summary of the neural network with the summary method on the Keras model. When you run that, it will print a nicely-formatted summary that contains all of the network layers and a number that represents the total trainable weights in the network.
[00:19] In general, the more weights a network has, the more complex the function it can approximate, but also, the longer it will take to train and the more data you will need to properly learn that function.
[00:32] We can change the neural network by modifying the number of nodes in a layer, or by modifying the network entirely, to get a better feel for how complex the network is, and how many trainable weights it contains.
[00:52] You can also use this summary method on networks that you didn't define yourself. It can be a helpful way to explore pre-trained networks.
Member comments are a way for members to communicate, interact, and ask questions about a lesson.
The instructor or someone from the community might respond to your question Here are a few basic guidelines to commenting on egghead.io
Be on-Topic
Comments are for discussing a lesson. If you're having a general issue with the website functionality, please contact us at support@egghead.io.
Avoid meta-discussion
Code Problems?
Should be accompanied by code! Codesandbox or Stackblitz provide a way to share code and discuss it in context
Details and Context
Vague question? Vague answer. Any details and context you can provide will lure more interesting answers!