Keys to clean and accurate training data
Our methodology based on years of research and unique industry expertise can help you successfully tap into the wisdom of the crowd on a large scale. If you want to efficiently use the knowledge of thousands of people to get clean and accurate data for your ML needs, follow our tips for each of these essential steps.
1. Decomposition
Break your task down into steps until each separate level is clear enough for any performer to handle.

2. Instructions
The more comprehensive the instructions, the more accurate the results. 

3. Interfaces
A good interface makes it easy for users to perform the same repeated actions quickly and correctly. 

4. Quality control
Carefully plan and configure a quality control system to ensure high-quality results. 
5. Pricing
Find the optimal price based on speed and quality.

6. Results
After the pool is finished, aggregate the results and check statistics.

Application for corporate training

We offer corporate training to help you solve existing challenges and develop an internal team of crowd science architects (CSA). 
Useful resources 
Learn about Toloka technologies, new features, and success stories.
Public datasets
Use our datasets for your projects or collect your own data that meets your needs.
Integrate on-demand global crowdforce & build fully automated ML pipelines.
Python library
We have an open-sourced library with a client that covers all API functionalities.
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Tue Jun 01 2021 10:46:24 GMT+0300 (Moscow Standard Time)