Understanding Data Preparation in AI Projects

Data preparation is crucial for analytics and machine learning projects, involving activities like data cleaning, transformation, wrangling, and augmentation. This ensures data is usable and accurate for analysis. Data cleaning deduplicates and removes irrelevant or bad data, a vital step in optimizing model performance. Additionally, processes like data manipulation, normalization, and merging help streamline data for effective AI utilization.