Pro Deep Learning with TensorFlow 2.0: A Mathematical Approach to Advanced Artificial Intelligence in Python

© The Author(s), under exclusive license to APress Media, LLC, part of Springer Nature 2023

S. PattanayakPro Deep Learning with TensorFlow 2.0https://doi.org/10.1007/978-1-4842-8931-0_5

5. Unsupervised Learning with Restricted Boltzmann Machines and Autoencoders

Santanu Pattanayak¹  

(1)

Prestige Ozone, Bangalore, Karnataka, India

 

Unsupervised learning is a branch of machine learning that tries to find hidden structures within unlabeled data and derive insights from it. Clustering, data dimensionality-reduction techniques, noise reduction, segmentation, anomaly detection, fraud detection, and other rich methods rely on unsupervised learning to drive analytics. Today, with so much data around us, it is impossible to label all data for supervised learning. ...