The Essential Guide to Training Data

The Essential Guide to
Training Data

Training data is a resource used by engineers to develop machine learning models. It’s used to train algorithms by providing them with comprehensive, consistent information about a specific task. Training data is usually composed of a large number of data points, each formatted with labels and other metadata.

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How you build, format, and annotate your training dataset has a direct impact on the model you create. In fact, poorly processed data is one of the most common reasons that machine learning projects fail.

However, if you haven’t worked with training data before, it can be difficult to know where to start. After all, data can be surprisingly complex. It’s hard to figure out what a dataset should look like and how to improve it.

We created this guide to help you address some of these important issues. In this in-depth piece, we’ll look at what training data is, where you can get it, and how you can improve it.

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