jaime.lucero

Before machine learning (ML) models can generate predictions or insights, the raw data must first be cleaned, organized, and transformed into a suitable format for the model. This process is known as data preprocessing. It is the foundation of every successful ML project. It ensures that the model learns from high-quality, consistent, and well-structured input rather than noisy, incomplete, or biased information. In this hands-on guide, we’ll walk through how to transform a raw Kindle eBook dataset from Kaggle into machine learning-ready data using Google Colab, a free cloud-based environment that allows you to write and execute Python code directly [...]