Data Labeling for ML

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Data Labeling can be very confusing. Help us prepare an article about it by answering a few questions. As a thank you, we will send you a cheat sheet with 40+ useful resources that help you understand and organize data labeling.

Email *

1. Which country are you based in? *

2. How are you involved in data science, ML or AI? *

I use ML algorithms in the context of data exploration, analysis, and reporting

I am a computer science or data science student

I train and deploy ML algorithms in my app, project or product

I train models for others (my team or clients) to deploy

Other:

Required

3. How familiar are you with preparing data for Machine Learning and AI? *

Very familiar

Have some experience

Always relied on open source datasets

Know very little about it

Don’t know anything about it

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