Models and Algorithms for Unsupervised Learning

Models and Algorithms for Unsupervised Learning introduces mathematical techniques, key algorithms, and Python implementations that will help you build machine learning models for unannotated data.Youll master everything from kmeans and hierarchical clustering, to advanced neural networks like GANs and Restricted Boltzmann Machines.
Youll learn the business use case for different models, and master best practices for structured, text, and image data. Each new algorithm is introduced with a case study for retail, aviation, banking, and moreand youll develop a Python solution to fix each of these real-world problems. At the end of each chapter, youll find quizzes, practice datasets, and links to research papers to help you lock in what youve learned and expand your knowledge.