{"product_id":"practical-guide-to-applied-conformal-prediction-in-python-learn-and-apply-the-best-uncertainty-frameworks-to-your-industry-applications-paperback","title":"Practical Guide to Applied Conformal Prediction in Python: Learn and apply the best uncertainty frameworks to your industry applications - Paperback","description":"\u003cdiv\u003e\u003cp style=\"text-align: right;\"\u003e\u003ca href=\"https:\/\/reportcopyrightinfringement.com\/\" target=\"_blank\" rel=\"nofollow\"\u003e\u003cb\u003eReport copyright infringement\u003c\/b\u003e\u003c\/a\u003e\u003c\/p\u003e\u003c\/div\u003e\u003cp\u003eby \u003cb\u003eValery Manokhin\u003c\/b\u003e (Author)\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eElevate your machine learning skills using the Conformal Prediction framework for uncertainty quantification. Dive into unique strategies, overcome real-world challenges, and become confident and precise with forecasting.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eKey Features: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eMaster Conformal Prediction, a fast-growing ML framework, with Python applications\u003c\/li\u003e\n\u003cli\u003eExplore cutting-edge methods to measure and manage uncertainty in industry applications\u003c\/li\u003e\n\u003cli\u003eUnderstand how Conformal Prediction differs from traditional machine learning\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eBook Description: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eIn the rapidly evolving landscape of machine learning, the ability to accurately quantify uncertainty is pivotal. The book addresses this need by offering an in-depth exploration of Conformal Prediction, a cutting-edge framework to manage uncertainty in various ML applications.\u003c\/p\u003e\u003cp\u003eLearn how Conformal Prediction excels in calibrating classification models, produces well-calibrated prediction intervals for regression, and resolves challenges in time series forecasting and imbalanced data. Discover specialised applications of conformal prediction in cutting-edge domains like computer vision and NLP. Each chapter delves into specific aspects, offering hands-on insights and best practices for enhancing prediction reliability. The book concludes with a focus on multi-class classification nuances, providing expert-level proficiency to seamlessly integrate Conformal Prediction into diverse industries. With practical examples in Python using real-world datasets, expert insights, and open-source library applications, you will gain a solid understanding of this modern framework for uncertainty quantification.\u003c\/p\u003e\u003cp\u003eBy the end of this book, you will be able to master Conformal Prediction in Python with a blend of theory and practical application, enabling you to confidently apply this powerful framework to quantify uncertainty in diverse fields.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWhat You Will Learn: \u003c\/strong\u003e\u003c\/p\u003e\u003cul\u003e\n\u003cli\u003eThe fundamental concepts and principles of conformal prediction\u003c\/li\u003e\n\u003cli\u003eLearn how conformal prediction differs from traditional ML methods\u003c\/li\u003e\n\u003cli\u003eApply real-world examples to your own industry applications\u003c\/li\u003e\n\u003cli\u003eExplore advanced topics - imbalanced data and multi-class CP\u003c\/li\u003e\n\u003cli\u003eDive into the details of the conformal prediction framework\u003c\/li\u003e\n\u003cli\u003eBoost your career as a data scientist, ML engineer, or researcher\u003c\/li\u003e\n\u003cli\u003eLearn to apply conformal prediction to forecasting and NLP\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWho this book is for: \u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003eIdeal for readers with a basic understanding of machine learning concepts and Python programming, this book caters to data scientists, ML engineers, academics, and anyone keen on advancing their skills in uncertainty quantification in ML.\u003c\/p\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eNumber of Pages:\u003c\/strong\u003e 240\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003eDimensions:\u003c\/strong\u003e 0.51 x 9.25 x 7.5 IN\u003c\/div\u003e\n            \u003cdiv\u003e\n\u003cstrong\u003ePublication Date:\u003c\/strong\u003e December 20, 2023\u003c\/div\u003e\n            ","brand":"Books by splitShops","offers":[{"title":"Default Title","offer_id":50345546744045,"sku":"9781805122760","price":74.86,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0020\/8918\/9441\/files\/8tjwdT8Rvt9781805122760.webp?v=1785207696","url":"https:\/\/www.webster.direct\/products\/practical-guide-to-applied-conformal-prediction-in-python-learn-and-apply-the-best-uncertainty-frameworks-to-your-industry-applications-paperback","provider":"Webster.Direct","version":"1.0","type":"link"}