Uncover What Deep CNNs Are Doing With Python and Tensorflow

Explore the inner workings of Deep Convolutional Neural Networks (CNNs) using Python and TensorFlow in this 41-minute tutorial video. Gain insights into visualizing outputs from intermediate CNN layers to understand how computer vision models make predictions. Follow along as the instructor guides you through importing dependencies, loading a trained model, accessing layers, creating an intermediate model, and loading images. Learn to make predictions with the intermediate model, visualize outputs, and create visualization grids. Discover techniques for visualizing different layers to gain a deeper understanding of CNN functionality. Access the provided GitHub repository for the complete code and join the discussion on various social media platforms for further engagement and support.

- Start
- Explainer
- Code
- Import Dependencies
- Load a Trained Model
- Accessing Layers
- Creating an Intermediate Model
- Load an Image
- Predictions with the Intermediate Model
- Visualising the Output
- Create a Viz Grid
- Visualising Different Layers
- Ending