{"product_id":"9781617296741","title":"Human-in-the-Loop Machine Learning: Active learning and annotation for human-centered AI","description":"\u003ctable\u003e\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eAuthor\/Contributor(s):\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eMonarch, Robert (Munro)\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003ePublisher:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003eManning\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eDate:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd\u003e7\/20\/2021\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eBinding:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003ePaperback\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003ctr\u003e\n\u003ctd style=\"\"\u003e\u003cstrong\u003eCondition:\u003c\/strong\u003e\u003c\/td\u003e\n\u003ctd style=\"\"\u003eNEW\u003cbr\u003e\n\u003c\/td\u003e\n\u003c\/tr\u003e\n\u003c\/tbody\u003e\u003c\/table\u003e\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\u003cbr\u003e\u003cbr\u003e\u003cb\u003eSummary\u003c\/b\u003e\u003cbr\u003eMost 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAbout the technology\u003c\/b\u003e\u003cbr\u003eMachine 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.\u003cbr\u003e\u003cbr\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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eWhat's inside\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003eIdentifying the right training and evaluation data\u003cbr\u003eFinding and managing people to annotate data\u003cbr\u003eSelecting annotation quality control strategies\u003cbr\u003eDesigning interfaces to improve accuracy and efficiency\u003cbr\u003e\u003cbr\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.\u003cbr\u003e\u003cbr\u003eRobert holds a PhD from Stanford focused on \u003ci\u003eHuman-in-the-Loop machine learning\u003c\/i\u003e 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cbr\u003ePART 1 - FIRST STEPS\u003cbr\u003e1 Introduction to \u003ci\u003ehuman-in-the-loop machine learning\u003c\/i\u003e\u003cbr\u003e2 Getting started with \u003ci\u003ehuman-in-the-loop machine learning\u003c\/i\u003e\u003cbr\u003ePART 2 - ACTIVE LEARNING\u003cbr\u003e3 Uncertainty sampling\u003cbr\u003e4 Diversity sampling\u003cbr\u003e5 Advanced active learning\u003cbr\u003e6 Applying active learning to different machine learning tasks\u003cbr\u003ePART 3 - ANNOTATION\u003cbr\u003e7 Working with the people annotating your data\u003cbr\u003e8 Quality control for data annotation\u003cbr\u003e9 Advanced data annotation and augmentation\u003cbr\u003e10 Annotation quality for different machine learning tasks\u003cbr\u003ePART 4 - HUMAN–COMPUTER INTERACTION FOR MACHINE LEARNING\u003cbr\u003e11 Interfaces for data annotation\u003cbr\u003e12 \u003ci\u003eHuman-in-the-loop machine learning\u003c\/i\u003e products","brand":"Manning","offers":[{"title":"Default Title","offer_id":48176680370431,"sku":"9781617296741","price":59.99,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0452\/0886\/2873\/files\/Jacket_b039010a-c3c3-4b99-beb0-6677d685e6df.jpg?v=1771351305","url":"https:\/\/massivebookshop.com\/de\/products\/9781617296741","provider":"MASSIVE BOOKSHOP","version":"1.0","type":"link"}