Frugal ML: Taking the cost and complexity out of ML

Read this whitepaper to understand:

  • The drivers of widespread ML adoption—and why 85% of ML projects fail
  • What Frugal ML is, and why it’s the right approach to enable your organization to achieve ML success
  • The 5 principles of Frugal ML and the associated practices you’ll need to master to adopt them
  • How Refract by Fosfor can facilitate a Frugal ML approach
  • How Standard Chartered Bank used Refract to enable Frugal ML-based approaches to successfully overcome model monitoring and execution challenges

This whitepaper aims to help enterprises evaluate their decision to adopt ML by addressing pain points and highlighting how Frugal Principles and Practices can contribute to success in solving their business problems through ML. We will explore in depth on the five principles of Frugal ML:

  1. Focus on the core
  2. First solve then scale
  3. Do more with less
  4. Keep it simple, and
  5. Think of outcomes, not outputs.

These principles can be your go-to guide for successfully developing and deploying ML solutions across your enterprise. By thinking and implementing a frugal approach to ML solutions, you can keep your cost and complexity low while significantly improving end-user experience and business outcomes.

Get the whitepaper

Composability for Decision Intelligence: Getting insights where you need them

Read this whitepaper to understand composability and how innovative companies are using it to make the power of Decision Intelligence more accessible to end users.

Read more

Explainable AI (XAI): A primer

Read this eBook to learn about Explainable AI (XAI) and its importance in the adoption of AI within enterprises.

Read more

The data mesh approach: Building a modern data organization

Read this whitepaper to learn how a data mesh approach can help organizations manage complex data infrastructure more efficiently.

Read more