Building and Training an Autoencoder in Keras - TensorFlow - Python

Learn to build and train autoencoders using Python, TensorFlow, and Keras in this comprehensive tutorial video. Explore the process of chaining encoder and decoder architectures to create an autoencoder, and gain hands-on experience training it with the MNIST dataset. Follow along as the instructor guides you through building the autoencoder, updating the summary method, implementing compile and train methods, and creating a training script. Discover insights into the MNIST dataset and observe the training process in action. By the end of this 27-minute tutorial, you'll have a solid understanding of autoencoder implementation and training techniques using popular deep learning frameworks.

Intro
Build autoencoder
Update summary method
Build compile method
Build train method
Create the train script
The MNIST dataset
Training the autoencoder
Performing a train run
What's up next?