CNN Explained with Code Building an Image Classifier on Google Colab Complete Step-By-Step Tutorial
Part 2 of our CNN series: we turn theory into practice — full code walkthrough and live run on Google Colab.
We’ll load CIFAR-10, build a simple but effective CNN with Keras, train it, evaluate, and visualize model attention using Grad-CAM.
What you’ll learn:
• How to set up Colab (mount Drive, install libs)
• Data preprocessing and augmentation
• Model architecture (Conv → ReLU → Pool → Dense)
• Training tips and hyperparameters
• Save & load models
• Grad-CAM: visualize what the CNN “looks at”
• Exporting results and common troubleshooting
Subscribe for Part 3 — advanced architectures and transfer learning.