{"product_id":"human-in-the-loop-machine-learning-active-learning-and-annotation-for-human-centered-ai-9781617296741","title":"Human-In-The-Loop Machine Learning: Active Learning and Annotation for Human-Centered AI","description":"\u003cb\u003e\u003ci\u003eHuman-in-the-Loop Machine Learning\u003c\/i\u003e lays out methods for humans and machines to work together effectively.\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e\u003cb\u003eSummary\u003c\/b\u003e\u003cbr\u003e Most machine learning systems that are deployed in the world today learn from human feedback. However, most machine learning courses focus almost exclusively on the algorithms, not the human-computer interaction part of the systems. This can leave a big knowledge gap for data scientists working in real-world machine learning, where data scientists spend more time on data management than on building algorithms. \u003ci\u003eHuman-in-the-Loop Machine Learning\u003c\/i\u003e is a practical guide to optimizing the entire machine learning process, including techniques for annotation, active learning, transfer learning, and using machine learning to optimize every step of the process. \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 Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eAbout the book\u003c\/b\u003e\u003cbr\u003e \u003ci\u003eHuman-in-the-Loop Machine Learning\u003c\/i\u003e lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to create training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows. \u003cp\u003e\u003c\/p\u003e \u003cb\u003eWhat's inside\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e Identifying the right training and evaluation data\u003cbr\u003e Finding and managing people to annotate data\u003cbr\u003e Selecting annotation quality control strategies\u003cbr\u003e Designing interfaces to improve accuracy and efficiency \u003cp\u003e\u003c\/p\u003e \u003cb\u003eAbout the author\u003c\/b\u003e\u003cbr\u003e \u003cb\u003eRobert (Munro) Monarch\u003c\/b\u003e is a data scientist and engineer who has built machine learning data for companies such as Apple, Amazon, Google, and IBM. He holds a PhD from Stanford. \u003cp\u003e\u003c\/p\u003eRobert holds a PhD from Stanford focused on Human-in-the-Loop machine learning for healthcare and disaster response, and is a disaster response professional in addition to being a machine learning professional. A worked example throughout this text is classifying disaster-related messages from real disasters that Robert has helped respond to in the past. \u003cp\u003e\u003c\/p\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003ePART 1 - FIRST STEPS\u003cbr\u003e 1 Introduction to human-in-the-loop machine learning\u003cbr\u003e 2 Getting started with human-in-the-loop machine learning\u003cbr\u003e PART 2 - ACTIVE LEARNING\u003cbr\u003e 3 Uncertainty sampling\u003cbr\u003e 4 Diversity sampling\u003cbr\u003e 5 Advanced active learning\u003cbr\u003e 6 Applying active learning to different machine learning tasks\u003cbr\u003e PART 3 - ANNOTATION\u003cbr\u003e 7 Working with the people annotating your data\u003cbr\u003e 8 Quality control for data annotation\u003cbr\u003e 9 Advanced data annotation and augmentation\u003cbr\u003e 10 Annotation quality for different machine learning tasks\u003cbr\u003e PART 4 - HUMAN-COMPUTER INTERACTION FOR MACHINE LEARNING\u003cbr\u003e 11 Interfaces for data annotation\u003cbr\u003e 12 Human-in-the-loop machine learning products\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e \u003ca href=\"https:\/\/sureshotbooks-com.myshopify.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=AUTH-10368038\"\u003eMonarch\u003c\/a\u003e\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Manning Publications\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 07\/20\/2021\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 424\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 1.60lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 6.10h x 7.30w x 0.90d\u003cbr\u003e\u003cb\u003eISBN13:\u003c\/b\u003e 9781617296741\u003cbr\u003e\u003cb\u003eISBN10:\u003c\/b\u003e 1617296740\u003cbr\u003e\u003cb\u003eBISAC Categories:\u003c\/b\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/sureshotbooks-com.myshopify.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/sureshotbooks-com.myshopify.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM094000\"\u003eData Science | Machine Learning\u003c\/a\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/sureshotbooks-com.myshopify.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/sureshotbooks-com.myshopify.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM079010\"\u003eHuman-Computer Interaction (HCI)\u003c\/a\u003e\u003cbr\u003e- \u003ca href=\"https:\/\/sureshotbooks-com.myshopify.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=CAT-COM\"\u003eComputers\u003c\/a\u003e | \u003ca href=\"https:\/\/sureshotbooks-com.myshopify.com\/search?type=product%2Carticle%2Cpage\u0026amp;q=BISAC-COM044000\"\u003eData Science | Neural Networks\u003c\/a\u003e\u003cbr\u003e\u003cbr\u003e\u003cp\u003e\u003cb\u003eAbout the Author\u003c\/b\u003e\u003cbr\u003e\u003cb\u003eRobert (Munro) Monarch\u003c\/b\u003e is a data scientist and engineer who has built machine learning data for companies such as Apple, Amazon, Google, and IBM. He holds a PhD from Stanford. \u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e Robert holds a PhD from Stanford focused on Human-in-the-Loop machine learning for healthcare and disaster response, and is a disaster response professional in addition to being a machine learning professional. A worked example throughout this text is classifying disaster-related messages from real disasters that Robert has helped respond to in the past.","brand":"Manning Publications","offers":[{"title":"Default Title","offer_id":42711223697645,"sku":"9781617296741","price":79.98,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0550\/8097\/6621\/products\/img_d99ef80a-8a41-46bf-b2fb-64d2e8a8cfcb.jpg?v=1650157325","url":"https:\/\/sureshotbooks.com\/es\/products\/human-in-the-loop-machine-learning-active-learning-and-annotation-for-human-centered-ai-9781617296741","provider":"SureShot Books Publishing LLC","version":"1.0","type":"link"}