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Data Without Labels PDF

354 Pages·39 MB·English
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by Vaibhav Verdhan| 354 pages| 39| English

About Data Without Labels

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.Models and Algorithms for Unsupervised Learning teaches you to apply a full spectrum of machine learning algorithms to raw data. You’ll master everything from kmeans and hierarchical clustering, to advanced neural networks like GANs and Restricted Boltzmann Machines. You’ll 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 more-and you’ll develop a Python solution to fix each of these real-world problems. At the end of each chapter, you’ll find quizzes, practice datasets, and links to research papers to help you lock in what you’ve learned and expand your knowledge.

Detailed Information

Author:Vaibhav Verdhan
Pages:354
Language:English
File Size:39
Format:PDF
Price:FREE
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