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:

Focus on the core
First solve then scale
Do more with less
Keep it simple, and
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

Prompt Engineering: The New Era of AI

Trends are changing in the data science domain every day. Many tools, techniques, libraries, and algorithms are developing daily. This constantly changing landscape keeps the data science domain at the bleeding edge. The techniques and methods used to solve different tasks in Machine Learning (ML)/ Deep Learning (DL) and Natural Language Processing (NLP) are also changing.

Understanding the synergy between Augmented Analytics, Decision Intelligence, and Gen AI

As we delve into the current state of the analytics industry, one cannot overlook the transformative power of Augmented Analytics. Gartner's description of Augmented Analytics involves leveraging advanced technologies like Machine Learning and Artificial Intelligence to aid in data preparation, the generation of insights, and the explanation of those insights.

Using Decision Intelligence to enable environmental transparency

California’s Climate Corporate Data Accountability Act (CCDAA) is groundbreaking legislation in the US, aimed at promoting environmental transparency. This act sets forth reporting requirements and standards to ensure that corporations are held accountable for their greenhouse gas emissions.