Many data-intensive applications that use machine learning or artificial intelligence techniques depend on humans providing the initial dataset, enabling algorithms to process the rest or for other humans to evaluate the performance of such algorithms. Not only can labeled data for training and evaluation be collected faster, cheaper, and easier than ever before, but we now see the emergence of hybrid human-machine software that combines computations performed by humans and machines in conjunction. There are, however, real-world practical issues with the adoption of human computation and crowdsourcing. Building systems and data processing pipelines that require crowd computing remains difficult. In this book, we present practical considerations for designing and implementing tasks that require the use of humans and machines in combination with the goal of producing high-quality labels.
"synopsis" may belong to another edition of this title.
Omar Alonso is a Principal Data Scientist Lead at Microsoft in Silicon Valley where he works on the intersection of social media, information retrieval, knowledge graphs, and human computation. He holds a Ph.D. from the University of California at Davis and an undergraduate degree from UNICEN, Argentina.
"About this title" may belong to another edition of this title.
Seller: Brook Bookstore On Demand, Napoli, NA, Italy
Condition: new. Questo è un articolo print on demand. Seller Inventory # XTGHEUELUZ
Quantity: Over 20 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: New. Seller Inventory # 44573419-n
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 44573419
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In English. Seller Inventory # ria9783031011900_new
Quantity: Over 20 available
Seller: Chiron Media, Wallingford, United Kingdom
PF. Condition: New. Seller Inventory # 6666-IUK-9783031011900
Quantity: 10 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 44573419-n
Quantity: Over 20 available
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New. 1st edition NO-PA16APR2015-KAP. Seller Inventory # 26394683611
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 44573419
Quantity: Over 20 available
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Many data-intensive applications that use machine learning or artificial intelligence techniques depend on humans providing the initial dataset, enabling algorithms to process the rest or for other humans to evaluate the performance of such algorithms. Not only can labeled data for training and evaluation be collected faster, cheaper, and easier than ever before, but we now see the emergence of hybrid human-machine software that combines computations performed by humans and machines in conjunction. There are, however, real-world practical issues with the adoption of human computation and crowdsourcing. Building systems and data processing pipelines that require crowd computing remains difficult. In this book, we present practical considerations for designing and implementing tasks that require the use of humans and machines in combination with the goal of producing high-quality labels. 152 pp. Englisch. Seller Inventory # 9783031011900
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Condition: New. Seller Inventory # V9783031011900