Abstract
When building a deep learning model, it is often better to be able to visualize the model. Although the model we created—the LeNet model—is simple, it is better if we can see the structure. Especially when we are tweaking or modifying the model, we can easily compare their structures. And when working with more complex models (which we will look at in the next chapter), it is easier to wrap your head around them if you can see their structure visually.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
GitHub (Lutz Roeder), https://github.com/lutzroeder, [14 Nov, 2020].
- 2.
Github (Netron), https://github.com/lutzroeder/netron, [14 Nov, 2020].
- 3.
Github (Netron downloads), https://github.com/lutzroeder/netron/releases/latest, [14 Nov, 2020].
- 4.
Lutz Roeder (Netron browser version), https://www.lutzroeder.com/ai/netron, [14 Nov, 2020].
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2021 Thimira Amaratunga
About this chapter
Cite this chapter
Amaratunga, T. (2021). Visualizing Models. In: Deep Learning on Windows. Apress, Berkeley, CA. https://doi.org/10.1007/978-1-4842-6431-7_6
Download citation
DOI: https://doi.org/10.1007/978-1-4842-6431-7_6
Published:
Publisher Name: Apress, Berkeley, CA
Print ISBN: 978-1-4842-6430-0
Online ISBN: 978-1-4842-6431-7
eBook Packages: Professional and Applied ComputingApress Access BooksProfessional and Applied Computing (R0)