Mastering Unlabeled Data (MEAP V5)

Description

Discover all-practical implementations of the key algorithms and models for handling unlabeled data. Full of case studies demonstrating how to apply each technique to real-world problems. In Mastering Unlabeled Data you’ll learn: Fundamental building blocks and concepts of machine learning and unsupervised learning Data cleaning for structured and unstructured data like text and images Unsupervised time series clustering, Gaussian Mixture models, and statistical methods Building neural networks such as GANs and autoencoders How to interpret the results of unsupervised learning Choosing the right algorithm for your problem Deploying unsupervised learning to production Business use cases for machine learning and unsupervised learning Copyright_2022_Manning_Publications welcome 1_Introduction_to_machine_learning 2_Clustering_techniques 3_Dimensionality_reduction 4_Association_rules 5_Clustering_(advanced) 6_Dimensionality_reduction_(advanced) 7_Unsupervised_learning_for_text_data (4 more chapters planned)