PirateBay Download | verdhan v unsupervised learning generative ai 2023

verdhan v unsupervised learning generative ai 2023

Type:: E-books
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Size:: 27.9 MB
Uploaded On:: Nov. 22, 2023, 9:07 a.m.
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Textbook in PDF format 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 Unsupervised Learning with Generative AI 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 Clustering algorithms like kmeans, hierarchical clustering, DBSCAN, Gaussian Mixture Models, and Spectral clustering Dimensionality reduction methods like Principal Component Analysis (PCA), SVD, Multidimensional scaling, and t-SNE Association rule algorithms like aPriori, ECLAT, SPADE Unsupervised time series clustering, Gaussian Mixture models, and statistical methods Building neural networks such as GANs and autoencoders Dimensionality reduction methods like Principal Component Analysis and multidimensional scaling Association rule algorithms like aPriori, ECLAT, and SPADE Working with Python tools and libraries like sklearn, bumpy, Pandas, matplotlib, Seaborn, Keras, TensorFlow, andFflask How to interpret the results of unsupervised learning Choosing the right algorithm for your problem Deploying unsupervised learning to production 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. about the technology Unsupervised learning and Machine Learning algorithms draw inferences from unannotated data sets. The self-organizing approach to machine learning is great for spotting patterns a human might miss. about the book 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. about the reader For developers and data scientists. Basic Python experience required

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Verdhan V. Models and Algorithms for Unlabeled Data 2023.pdf 8.6 MB
Verdhan V. Supervised Learning with Python...2020.pdf 9.2 MB
Verdhan V. Unsupervised Learning with Generative AI 2023.pdf 10.1 MB

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verdhan v unsupervised learning generative ai 2023

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