Training Data for Machine Learning is popular PDF and ePub book, written by Anthony Sarkis in 2023-11-08, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Training Data for Machine Learning can be Read Online from any device for your convenience.
Training Data for Machine Learning Book PDF Summary
Your training data has as much to do with the success of your data project as the algorithms themselves because most failures in AI systems relate to training data. But while training data is the foundation for successful AI and machine learning, there are few comprehensive resources to help you ace the process. In this hands-on guide, author Anthony Sarkis--lead engineer for the Diffgram AI training data software--shows technical professionals, managers, and subject matter experts how to work with and scale training data, while illuminating the human side of supervising machines. Engineering leaders, data engineers, and data science professionals alike will gain a solid understanding of the concepts, tools, and processes they need to succeed with training data. With this book, you'll learn how to: Work effectively with training data including schemas, raw data, and annotations Transform your work, team, or organization to be more AI/ML data-centric Clearly explain training data concepts to other staff, team members, and stakeholders Design, deploy, and ship training data for production-grade AI applications Recognize and correct new training-data-based failure modes such as data bias Confidently use automation to more effectively create training data Successfully maintain, operate, and improve training data systems of record
Detail Book of Training Data for Machine Learning PDF
- Author : Anthony Sarkis
- Release : 08 November 2023
- Publisher : "O'Reilly Media, Inc."
- ISBN : 9781492094494
- Genre : Computers
- Total Page : 332 pages
- Language : English
- PDF File Size : 17,8 Mb
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