In this repo, I share my practice in implementing a deep convolutional denoising autoencoder for MNIST images.
- Data Preparation
- Load Data
- Scale and Reshape the Data
- Add Noise to the Data
- Denoising Autoencoder
- Build Encoder Model
- Build Decoder Model
- Train the Autoencoder
- Results
- Reference