Machine Learning Times
Machine Learning Times
A University Curriculum Supplement to Teach a Business Framework for ML Deployment
    In 2023, as a visiting analytics professor...
The AI Playbook: Providing Important Reminders to Data Professionals
 Originally published in DATAVERSITY. This article reviews the new...
Decode the Algorithm: Navigate the World of Machine Learning in Business with ‘The AI ​​Playbook’
  This article reviews the new book, The AI Playbook, by...
To Deploy Machine Learning, You Must Manage Operational Change—Here Is How UPS Got It Right
 Originally published in Harvard Data Science Review. For more...

2 years ago
Models Are Rarely Deployed – an Industrywide Failure in ML Leadership (Poll Results)

  Originally published in KDnuggets. The latest KDnuggets poll reconfirms today’s dire industry buzz: Very few machine learning models actually get deployed. In this article, I’ll summarize the poll results and argue that this pervasive failure of ML projects comes from a lack of prudent leadership. I’ll also argue that MLops is not the fundamental missing ingredient – instead, an effective ML leadership practice must be the dog that wags the model-integration tail. Considering the growing chatter about ML’s failure to launch, there’s been relatively little concrete industry research – especially when it comes to surveys on model

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