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What we learned labeling 1 million images


 
 
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In this guide you'll learn how to scope a computer vision project, what kind of source data you need to make it successful, what kind of tools fit your project best, and a whole lot more.



Sponsored Post.

 
 

At CrowdFlower, we've labeled over a million images, helping some of the world's most innovative companies power and validate their computer vision models. We put together a practical guide to share what we've learned along the way. 

In this guide you'll learn how to scope a computer vision project, what kind of source data you need to make it successful, what kind of tools fit your project best, and a whole lot more.

Some highlights from the eBook:

  • When it comes to training data, it's not just about quality. It's about quantity too.
  • Overfitting is a real problem with computer vision models. Find out how to solve it.
  • Simple image classification can be just as important as meticulous pixel labeling, if not more.
  • Every tool and strategy has its pros and cons. Learn how to decide which is right for you.

Download the guide.png

Download What We Learned Labeling 1 Million Images today to help you get started on your project and please reach out to me directly with any questions. 

Best regards,

Randi Barshack
VP, Marketing | CrowdFlower
rbarshack@crowdflower.com