ARTICLES

Feature Engineering for Fraud Detection

Feature Engineering for Fraud Detection

Introduction Fraud detection is critical in keeping remediating fraud and services safe and functional. First and foremost, it helps to protect businesses and individuals from financial loss. By identifying potential instances of fraud, companies can take steps to...

Machine Learning at the Edge: Elements Needed for Scale

Machine Learning at the Edge: Elements Needed for Scale

Learn about the elements you need to build an efficient, scalable edge ML architecture. There are four components that can help bring order to the chaos that is running ML at the edge and allow you to build an efficient, scalable edge ML architecture: Central...

When Machine Learning meets privacy

When Machine Learning meets privacy

Weekly talks and fireside chats about everything that has to do with the new space emerging around DevOps for Machine Learning aka MLOps aka Machine Learning Operations. This posted has been republished by AIIA. To listen to the original podcast, please click HERE....

Centaur at Work: Writing a Newsletter

Centaur at Work: Writing a Newsletter

A Story of Many Failures and One Success In this blog, join me as I embark on the complex journey of semi-automating an AI-focused weekly newsletter. You'll get a first-hand look at a diverse set of tools and tactics that I've put to work on this real-life puzzle....

How To Fine-Tune Hugging Face Transformers on a Custom Dataset

How To Fine-Tune Hugging Face Transformers on a Custom Dataset

Language models have come a long way in recent years, and their capabilities have expanded rapidly. With the right prompt, a language model can generate text that is almost indistinguishable from what a human would produce. In this post, we'll explore the art of...

Reducing GPU Costs for Production AI

Reducing GPU Costs for Production AI

This tech talk explores how you can efficiently use GPU resources for production inference. There are several ways to reduce GPU costs for production AI, including using cost-effective GPU options, using cloud providers, using containerization, using GPU acceleration...

The Only 3 ML Tools You Need

The Only 3 ML Tools You Need

Image by Author At a rapid pace, many machine learning techniques have moved from proof of concepts to powering crucial pieces of technology that people rely on daily. In attempts to capture this newly unlocked value, many teams have found themselves caught up in the...

Seven Reasons Why Realtime Machine Learning Is Here To Stay

Seven Reasons Why Realtime Machine Learning Is Here To Stay

A very powerful trend is playing out right now — more and more top tech companies are making a larger part of their machine learning as realtime as possible. So much so that many are skipping the offline phase [1] and directly starting with realtime ML systems. More...

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