Category: Data Preprocessing

In this post, we will look at a common way to deal with categorical values (e.g., small, medium, large). Most machine learning algorithms work with numerical values, so we need … Read More

One of data cleaning processes is about dealing with missing values. It is very common to find missing values in your datasets. To train your model better, you need to … Read More

Feature scaling is one of most important feature engineerings for many machine learning algorithms (Decision trees don’t need feature scaling necessarily). Most of the algorithms require similar scales for numerical … Read More

Have you seen this problem in your dataset? You might see the imbalanced classes problem when you deal with classification problems. This is very common. Imagine that you create a … Read More