The Importance Of Data In Machine Learning

Data is the lifeblood of machine learning and plays a crucial role in the process. Data can come in various forms and is collected from diverse sources. Data preprocessing, feature engineering, and training are all essential steps in the machine learning process. Validation data is used to assess the model’s performance and the model can then be deployed for making predictions or classifications on new, unseen data. Data is essential but also presents several challenges.