Image by Author Feature engineering is an important step in the machine learning pipeline. It is the process of transforming data in its native format into meaningful features to help the machine learning model learn better from the data. If done right, feature engineering can significantly enhance the performance of machine learning algorithms. Beyond the basics of understanding your data and preprocessing, effective feature engineering involves creating interaction terms, generating indicator variables, and binning features into buckets. These techniques help […]

Image by Author Using machine learning to solve real-world problems is exciting. But most eager beginners jump straight to model building—overlooking the fundamentals—resulting in models that aren’t very helpful. From understanding the data to choosing the best machine learning model for the problem, there are some common mistakes that beginners often tend to make. But before we go over them, you should understand the problem—it is step 0 if you will—you are trying to solve. Ask yourself enough questions to […]