Dataset is a collection (a “set”) of different types of data in a digital format. Data is the most important component of every Artificial Intelligence project. Datasets are typically made up of photographs, texts, audio, videos, etc., and are used to solve different Artificial Intelligence tasks including image or video classification, face recognition, object detection, sentiment analysis, stock market prediction, and much more.
A dataset is typically utilized for more than just training. A single processed training dataset is frequently divided into pieces, which is required to determine how successfully the model was trained. A testing dataset is often isolated from the data for this reason. Next, a not strictly necessary validation dataset can help you avoid training your algorithm on the same sort of data and producing biased predictions.
However, most of nowadays ML tasks, including those we solve at Tensorway, are solved with already existing datasets.
Tabular data refers to information organized into rows and columns, like a spreadsheet. Each row represents a single observation or record and each column represents a specific attribute or feature.
Unstructured data refers to information that does not adhere to a predefined data model or is not organized in a pre-defined manner.