Data collection is where every machine learning project begins, and it’s arguably the most important step. High-quality, diverse, and ethically sourced data sets the stage for successful model development and deployment. By understanding the nuances of data collection and applying best practices, you can ensure that your machine learning models are built on a strong, reliable foundation that leads to more accurate, unbiased, and effective results.