Globose Technology Solutions Pvt Ltd

Data annotation process involves from collection of data to labeling, quality check and validation that makes the raw data usable for machine learning training. For supervised machine learning projects, without labeled data, it is not possible to train the AI model. 1. Collecting Data One of the key components for any machine learning project is to collect data in an efficient manner. If data is not collected in the right way, it will create a lot of issues for the people working on the project. The data must be accurate, clean and the use of the data must be, structured. Data can be used in many applications, however in AI projects, the data itself and the algorithms applied on it are the most important. For data preparation, the process is based on statistical learning method and the data is manually labeled using a labeled data set. Data is marked manually and put into the central collection, which then is a large collection of labeled data, which the AI algorithms can use. 2. Label...