×

Don't get stuck in POC. Get your models to production!

First Name
Last Name
Company Name
Job Title
!
Thank you!
Error - something went wrong!
   

How to Deploy and Future-Proof Your Models: From Theory to Production

Data scientists are painfully familiar with the frustration of great machine learning models that were doomed to be stuck in the POC stage. It’s no secret that while most organizations understand the importance of machine learning models, most initiatives never make it off the ground, or produce the impact they were designed to provide. 

How can you avoid this fate, and push your machine learning models all the way to deployment? It’s all about understanding the pitfalls that await most ML initiatives and planning to avoid them. It’s about rethinking the development cycle, and understanding that you need to plan for tomorrow, not today. 

This guide discusses: 

  • The common pitfalls when planning a new ML project and how to avoid them  

  • How to  plan for models that will be scalable and adaptable

  • Four steps you can take to start building models that will go from theory to deployment faster

Previous Article
How Will Data Privacy Look in The Future?
How Will Data Privacy Look in The Future?

Data privacy continues to be a major hurdle for risk officers. In this article, we explain how the global i...

Next Article
Reframing the Connection Between Data Science and Automation
Reframing the Connection Between Data Science and Automation

Automation and data science are a match made in heaven. It's up to data leaders to understand how to introd...