Tensorflow: Building Autoencoders in TensorFlow
Overview/Description
Expected Duration
Lesson Objectives
Course Number
Expertise Level
Overview/Description
Explore how to perform dimensionality reduction using powerful unsupervised learning techniques such as Principal Components Analysis and autoencoding.

Expected Duration (hours)
0.8

Lesson Objectives Tensorflow: Building Autoencoders in TensorFlow

recognize how patterns help encode data
define how autoencoders work
recognize how principal component analysis works for dimensionality reduction
process data to perform principal component analysis
implement dimensionality reduction using principal component analysis with scikit-learn
apply autoencoders to perform principal component analysis
identify how to use the Fashion MNIST dataset for dimensionality reduction
apply autoencoders to images to reconstruct them from lower dimensionality representations
define how autoencoders work and their use cases

Course Number: it_sdaidt_08_enus

Expertise Level
Intermediate