Machine learning (ML) has become a core technology ingredient for organizations to drive real-world innovation, yet many are struggling to bring more ML models into production in a repeatable and responsible way. These organizations understand ML innovation, but face challenges like disparate, complex tools, concerns about how to keep data and ML models secure, and a common way to work with data science and business teams.
This eBook, High-Performance, Low-Cost Machine Learning for Any Use Case, explains how to achieve ML development at scale with an end-to-end solution that lowers costs—while delivering a standard practice that empowers more people and teams to use ML, regardless of their ML skill level.