In training artificial intelligence, selecting the right material is an essential step.
If you are now busy creating your artificial intelligence, then you are definitely wondering what to "feed" it with. You surely know that many data is publicly available. And we will not make a secret out of it. But still, you probably have strict database requirements because not all databases are suitable for your system.
How to create high quality datasets with FindDataLab
Formulate your requirements
Describe your needs. Check out our guide to learn what information we expect from you. Our data engineers will carefully examine your request.
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Get the desired data
Start to feed your system with high quality data.
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important steps in working with data foR ML
Data collection The quality and quantity of the data ultimately affect the accuracy of the result. It is important to remember that more data doesn't always mean better results. Every project is unique. Good data quality helps you achieve accurate results.
Data preparation It may seem that data collection is sufficient, but it is the opposite. Training dataset and test dataset are two interrelated entities. But each of them has its characteristics in structure.