With global spending on AI and machine learning forecast to eclipse $85 billion this year and $204 billion in 2025, enterprises are investing in ML infrastructure with urgency as AI becomes more critical to their organizations. Unfortunately, the burgeoning ML infrastructure market can be confusing, crowded and complex — a dizzying array of platforms and tools that even sophisticated ML teams struggle to keep straight.
In this comprehensive ebook, Arize AI breaks down the model building workflow to provide a comprehensive crash course on the major categories of solutions and why a team might need each. Designed to be useful to both business readers and dev teams broadly, this ebook details the goals and challenges in each stage of the machine learning workflow and the array of companies vying to help across:
- Data Preparation
- Model Building & Development Tools
- Model Validation
- Model Serving