FAQ: Image Classification - Adding Convolutional Layers to Your Model

This community-built FAQ covers the “Adding Convolutional Layers to Your Model” exercise from the lesson “Image Classification”.

Paths and Courses
This exercise can be found in the following Codecademy content:

Build Deep Learning Models with TensorFlow

FAQs on the exercise Adding Convolutional Layers to Your Model

There are currently no frequently asked questions associated with this exercise – that’s where you come in! You can contribute to this section by offering your own questions, answers, or clarifications on this exercise. Ask or answer a question by clicking reply (reply) below.

If you’ve had an “aha” moment about the concepts, formatting, syntax, or anything else with this exercise, consider sharing those insights! Teaching others and answering their questions is one of the best ways to learn and stay sharp.

Join the Discussion. Help a fellow learner on their journey.

Ask or answer a question about this exercise by clicking reply (reply) below!
You can also find further discussion and get answers to your questions over in Language Help.

Agree with a comment or answer? Like (like) to up-vote the contribution!

Need broader help or resources? Head to Language Help and Tips and Resources. If you are wanting feedback or inspiration for a project, check out Projects.

Looking for motivation to keep learning? Join our wider discussions in Community

Learn more about how to use this guide.

Found a bug? Report it online, or post in Bug Reporting

Have a question about your account or billing? Reach out to our customer support team!

None of the above? Find out where to ask other questions here!

I dont understand how the 8 newly created “images” after the first 8 5x5 filters is processed afterwards.

codecademy is quoting “The number of filters used in the previous layer becomes the number of channels that we input into the next!”

so how do i pass in 8 channels into 4 filters in the next step? Does every filter go on every channel from the input or is the volume just moved from the front to the back, thus not every filter is applied on every input-channel?

Andrew Ng states in his course (https://www.coursera.org/lecture/convolutional-neural-networks/convolutions-over-volume-ctQZz), that the amount of filters used must match the amount of channels from the input, which is not the case in this example here (8!=4).

Any help is highly appreciated! Thanks :slight_smile: