Acquiring Data

Acquiring Data or Data Acquisition refers to the procedure of collecting the required data. The process typically comprises three key steps:

Data Discovery: In this step, we search the data required for any AI Model. For example- To make a model for a self-driving car, we will require pictures of roads and the objects on roads. Therefore, we can search and download data from the internet. This process is called data discovery

Data Augmentation: It means increasing the amount of data by adding copies of existing data with small changes. In this step, the required images does not change, but we get more image by changing different parameters like color and brightness.

Data Generation: It refers to generating or recording data using sensors. The recorded data is stored in a computer in a suitable form. For example - Recording the temperature readings of a building.

Sources of Data

Primary Data Sources: Some of the sources for primary data include surveys, interviews, experiments, etc. The data generated from the experiment is an example of primary data.

Secondary Data Sources: Secondary data collection obtains information from external sources. Some sources are Google Data Search, Kaggle (Online community of Data Scientists), Government dataset (.gov), UCI (Machine Learning Repository), etc.

Web Scraping: The process of collecting data from websites using software is known as Web Scraping.