Labelbox

Training data quality is critical for a machine learning model’s performance. Quality is measured by both the consistency and the accuracy of labeled data. The industry standard methods for calculating training data quality are benchmarks (aka gold standard), consensus, and review. As a data scientist in AI, an essential part of your job is figuring out what combination of these quality assurance procedures is right for your project.

How to Measure Quality when Training Machine Learning Models

In order for data science teams to outsource annotation to a managed workforce provider — also known as a Business Process Outsourcer (BPO) — they must first have the tools and infrastructure to store and manage their training data. Data management tools and infrastructure should support R&amp;D product management teams, outsourced labeling teams, and internal labeling and review teams working together in a single centralized place with fully transparent oversight.

How to Scale Training Data

Ready to learn how to train your AI in less than a day without writing a single line of code? If you are sitting on a pile of data that you want to make useful, but AI seems too daunting of a task to get started, then this article is for you. Or if you have experienced the trenches of AI and are ready to make the model training process a whole lot simpler and faster, you will also find this article eye-opening.

AI is More Accessible Than You Know

Is your model not performing well? Try digging into your data. Instead of getting marginal improvements in performance by searching for state-of-the-art models, drastically improve your model’s accuracy by improving the quality of your data.

It all Boils Down to the Training Data

September brought many new features and updates to Labelbox. But most notable is that the image annotation interface has undergone a massive upgrade.

Introducing best-in-class image annotation tools for computer vision applications

Explore how data annotation is crucial to generative AI success. Learn about tools, strategies, & best practices that enhance AI model performance, scalability.

The Critical Role of Data Annotation in Shaping the Future of Generative AI

I decided to try and recreate Windows 98 using nothing else apart from CSS and HTML.

Recreate Windows 98 With CSS

70-Page Report on the COCO Dataset and Object Detection [Part 3]

Labelbox is the simplest platform to train and operate machine intelligence

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Since n.d.

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EVERGREEN INDEX #6501

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