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

PLEASE NOTE THAT THE ITEM IS THE E-BOOK WILL BE SENT VIA AN EMAIL IN LINK FORM WITHIN 24 HOURS OF PAYMENT. PLEASE DONT BID IF YOU INTEND NOT TO PAY

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 applications Integrate with a growing ecosystem of tools Recognize and correct new training data-based failure modes Improve existing system performance and avoid development risks Confidently use automation and acceleration approaches to more effectively create training data Avoid data loss by structuring metadata around created datasets Clearly explain training data concepts