Learn how to train AI models

Datasets in AI are collections of structured or unstructured data used to train, validate, and test machine learning models. They can include various forms of data, such as text, images, audio, or numerical values, and are essential for teaching models to recognize patterns and make predictions. High-quality datasets that are diverse and representative are crucial for developing robust AI systems capable of generalizing well to new, unseen data. In this guide you can find information on what kind of datasets are commonly used, in which format are they stored in and where can you find such data sets to download

AI datasets

Datasets are essential for training and evaluating artificial intelligence (AI) systems because they provide the foundational information that models learn from. In the realm of machine learning, models rely on large volumes of data to identify patterns, make predictions, and generate insights. In the following list you can find a collection of datasets you can use for training AI, or to understand how training works.

  • Text
  • Image
  • Audio
  • Video
  • Time-series
  • Geospatial
  • 3D
  • Tabular

High-quality datasets enable AI to understand complex relationships within data, which is crucial for tasks like image recognition, natural language processing, and decision-making. Moreover, diverse and representative datasets help ensure that AI systems perform accurately across various scenarios and populations, minimizing biases and improving generalization. Without well-curated datasets, AI models would lack the necessary context and examples to function effectively, hindering their practical applications and overall reliability. Check out the formats these datasets come in:

AI data formats

  • json
  • csv
  • parquet
  • imagefolder
  • soundfolder
  • webdataset
  • text
  • arrow

More information