Deep Learning with PyTorch : GradCAM

Deep Learning with PyTorch : GradCAM: Overview & Verdict

Gradient-weighted Class Activation Mapping (Grad-CAM), uses the class-specific gradient information flowing into the final convolutional layer of a CNN to produce a coarse localization map of the important regions in the image. In this 2-hour long project-based course, you will implement GradCAM on simple classification dataset. You will write a custom dataset class for Image-Classification dataset. Thereafter, you will create custom CNN architecture. Moreover, you are going to create train func

Because it is hosted on Coursera, enrollment is permanent: claim it once and the lessons stay in your library even if the price returns later.

It is taught by Coursera, delivered in en — useful context when you are deciding whether Deep Learning with PyTorch : GradCAM fits the time you have this week.

What you need before starting

• • A free Coursera account (takes under a minute to create)
• • A laptop, tablet or phone with a stable internet connection
• • Basic computer literacy; everything specific to ai & machine learning is explained in the course

About Coursera

Coursera teaches Deep Learning with PyTorch : GradCAM. The lessons follow a consistent structure and the Q&A section stays active, which is a good signal of ongoing support.

Our verdict: A solid pick: you get the full paid course plus a certificate without spending anything. Enroll now even if you plan to start later — access stays with your account after the coupon expires.