دانلود کتاب Training Data for Machine Learning: Human Supervision from Annotation to Data Science

Your training data has as much to do with the success of your data project as the algorithms themselves--most failures in deep learning systems relate to training data. But while training data is the foundation for successful machine learning, there are few comprehensive resources to help you ace the process. This hands-on guide explains how to work with and scale training data. Data science professionals and machine learning engineers will gain a solid understanding of the concepts, tools, and processes needed to:Design, deploy, and ship training data for production-grade deep learning applicationsIntegrate with a growing ecosystem of toolsRecognize and correct new training data-based failure modesImprove existing system performance and avoid development risksConfidently use automation and acceleration approaches to more effectively create training dataAvoid data loss by structuring metadata around created datasetsClearly explain training data concepts to subject matter experts and other shareholdersSuccessfully maintain, operate, and improve your system