Unsupervised Learning with Generative AI by Vaibhav Verdhan (.ePUB)

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File Size: 10 MB

Unsupervised Learning with Generative AI (MEAP v7) by Vaibhav Verdhan
Requirements: .ePUB reader, 10 MB
Overview: 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. Unsupervised Learning with Generative AI introduces mathematical techniques, key algorithms, and Python implementations that will help you build machine learning models for unannotated data. You’ll discover hands-off and unsupervised machine learning approaches that can still untangle raw, real-world datasets and support sound strategic decisions for your business. Don’t get bogged down in theory—the book bridges the gap between complex math and practical Python implementations, covering end-to-end model development all the way through to production deployment. You’ll discover the business use cases for machine learning and unsupervised learning, and access insightful research papers to complete your knowledge. Unsupervised Learning with Generative AI 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. For developers and data scientists. Basic Python experience required.
Genre: Non-Fiction > Tech & Devices

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