Image by author (Arize AI)

Written in collaboration with Reah Miyara, Head of Product at Arize AI

The age-old saying still holds: the customer is always right, but some are more right than others (that’s the saying, right?). While there are many metrics to estimate the value of a customer within any organization, customer lifetime…

Image by author (Arize AI)

Written in collaboration with Amber Roberts, ML Sales Engineer at Arize AI

The adoption of machine learning (ML) has resulted in an array of artificial intelligence (AI) applications in the growing areas of language processing, computer vision, unsupervised learning and even autonomous systems.

As models increase in complexity, the ability…

Image by author (Arize AI)

Written in collaboration with Reah Miyara, Head of Product at Arize AI

Total digital ad spending is expected to reach $455.3 billion this year. Of that, 55.2% will go to display advertising and 40.2% will go to search. With digital formats commanding the lion’s share of ad dollars, marketers need…

Image by author (credit: Arize AI)

Written in collaboration with Reah Miyara, Head of Product at Arize AI

Demand forecasting is the time-tested discipline of using historical data, traditionally on purchases, to forecast customer demand over a given time period. Critical to operations and pricing strategy, nearly every category of business uses demand forecasting in some…

Image by author

Written in collaboration with Reah Miyara, Head of Product at Arize AI

Every year, fraud costs the global economy over $5 trillion. In addition to taking a deeply personal toll on individual victims, fraud impacts businesses in the form of lost revenue and productivity as well as damaged reputation and…

In the last decade, significant technological progress has been driven rapidly by numerous advances in applications of machine learning. Novel ML techniques have revolutionized industries by cracking historically elusive problems in computer vision, natural language processing, robotics, and many others. …

Alex Zamoshchin, Image by Author

Today, companies dedicate significant resources to implementing ML models, only to see a myriad of unexpected performance degradation issues arise when they are deployed.

To overcome these challenges, data organizations are increasingly turning to ML engineers to help bridge the gap between the data scientists that build the models and…

Notes from Industry

Image by Author

Written by Bob Nugman, ML Engineer at Doordash, and Aparna Dhinakaran, CPO of Arize AI. In this piece, Bob and Aparna discuss the importance of reliability engineering for ML initiatives.

Machine learning is quickly becoming a key ingredient in emerging products and technologies. This has caused the field to rapidly…

Aparna Dhinakaran

Co-Founder and CPO of Arize AI. Formerly Computer Vision PhD at Cornell, Uber Machine Learning, UC Berkeley AI Research.

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