{"product_id":"models-and-algorithms-for-unsupervised-vaibhav-verdhan-9781617298721","title":"Unsupervised Learning with Generative AI","description":"\u003cb\u003eDiscover all-practical implementations of the key algorithms and models for handling unlabelled data. Full of case studies demonstrating how to apply each technique to real-world problems.\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003eIn \u003ci\u003eUnsupervised Learning with Generative AI\u003c\/i\u003e you'll learn: \u003cp\u003e\u003c\/p\u003e \u003cul\u003e \u003cli\u003eFundamental building blocks and concepts of machine learning and unsupervised learning\u003c\/li\u003e \u003cli\u003eData cleaning for structured and unstructured data like text and images\u003c\/li\u003e \u003cli\u003eClustering algorithms like kmeans, hierarchical clustering, DBSCAN, Gaussian Mixture Models, and Spectral clustering\u003c\/li\u003e \u003cli\u003eDimensionality reduction methods like Principal Component Analysis (PCA), SVD, Multidimensional scaling, and t-SNE\u003c\/li\u003e \u003cli\u003eAssociation rule algorithms like aPriori, ECLAT, SPADE\u003c\/li\u003e \u003cli\u003eUnsupervised time series clustering, Gaussian Mixture models, and statistical methods\u003c\/li\u003e \u003cli\u003eBuilding neural networks such as GANs and autoencoders\u003c\/li\u003e \u003cli\u003eDimensionality reduction methods like Principal Component Analysis and multidimensional scaling\u003c\/li\u003e \u003cli\u003eAssociation rule algorithms like aPriori, ECLAT, and SPADE\u003c\/li\u003e \u003cli\u003eWorking with Python tools and libraries like sklearn, bumpy, Pandas, matplotlib, Seaborn, Keras, TensorFlow, andFflask\u003c\/li\u003e \u003cli\u003eHow to interpret the results of unsupervised learning\u003c\/li\u003e \u003cli\u003eChoosing the right algorithm for your problem\u003c\/li\u003e \u003cli\u003eDeploying unsupervised learning to production\u003c\/li\u003e \u003c\/ul\u003e \u003cbr\u003e\u003ci\u003eUnsupervised Learning with Generative AI\u003c\/i\u003e 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. \u003cp\u003e\u003c\/p\u003e 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. \u003cp\u003e\u003c\/p\u003e Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eAbout the technology\u003c\/b\u003e\u003cbr\u003e 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. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eAbout the book\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eUnsupervised Learning with Generative AI\u003c\/i\u003e 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. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eAbout the reader\u003c\/b\u003e\u003cbr\u003e For developers and data scientists. Basic Python experience required. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eAbout the author\u003c\/b\u003e\u003cbr\u003e \u003cb\u003eVaibhav Verdhan\u003c\/b\u003e is a seasoned data science professional with rich experience across geographies and domains. He has led multiple engagements in machine learning and artificial intelligence. A leading industry expert, Vaibhav is a regular speaker at conferences and meet-ups and mentors students and professionals. Currently he resides in Ireland where he works as a principal data scientist.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Vaibhav Verdhan\u003cbr\u003e\u003cb\u003eISBN-10:\u003c\/b\u003e 1617298727\u003cbr\u003e\u003cb\u003eISBN-13:\u003c\/b\u003e 9781617298721\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Manning Publications\u003cbr\u003e\u003cb\u003eLanguage:\u003c\/b\u003e English\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 07\/30\/2024\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 250\u003cbr\u003e\u003cb\u003eFormat:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.25h x 7.38w x 0.63d","brand":"Vaibhav Verdhan","offers":[{"title":"Paperback","offer_id":43945583608063,"sku":"9781617298721","price":59.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0662\/2982\/9887\/products\/img_076277d2-b76a-4e52-824f-eabf2cf191a4.jpg?v=1681508951","url":"https:\/\/www.whiterainbookhouse.com\/products\/models-and-algorithms-for-unsupervised-vaibhav-verdhan-9781617298721","provider":"WR Book House","version":"1.0","type":"link"}