AI data collection company – Short Explanation

Machine Learning (ML) can use data in a supervised state where the data is used to train a machine on whether a selection is right or wrong. Over time and many iterations, the machine learns the suitable patterns, so they can better make a judgment themselves. When training AI algorithms and systems, data is the critical requirement. This training data can be obtained from an AI data collection company.

AI data collection companies and its data services

There are many different data collection companies around the world. With AI training datasets for machine learning, almost 80% of the time is spent on data preparation.

Data collection images

With supervised or unsupervised machine learning, image data sets can play a very important role. With supervised learning, the algorithm is “taught” what is right or wrong so they quickly learn to identify the differences between a dog or a cat.

Unsupervised learning is a bit more involved, and the algorithm is not told what is right or wrong, or even if the image is valid or not. The algorithm learns by itself and creates different patterns based on the information that it has access to. In this instance, it might not understand the difference between a dog and cat but could identify all of the images where the animal had a black left ear.

When building a machine learning model, consider the quality of the images you provide to the algorithm. It is vital to have the best quality images in terms of resolution so that the algorithm can best understand all the essential elements.

Data collection services

Data collection services require a rigorous and defined process if they have any hope of being successful. Depending on the type of data being collected, the requirements could change as Image / Photo datasets and Video datasets collection is very different from Speech or audio datasets collection.

However, while some specific areas are unique, some similarities can be considered when looking at a data collection service.

At the start, the client needs to provide their specific requirements and any available samples. The requirements should detail what they expect as an outcome to understand what they are looking for.

The data collection service needs to review the provided samples to judge the quality and determine the collection method required to gather additional samples. For example, voice samples could be obtained through phone calls or recorded conversations, while images have a different requirement.

The next step is determining where the data will be stored and organizing the appropriate tools with the collection method decided upon. After this, the team can begin the process of collecting the data itself. In some cases, this might require acquiring additional trained resources.

With the data collected and compiled, it needs to be reviewed to ensure that it matches what the client requested, and if it does, it can then be shared with the client.