Welcome to the mysterious world of data standardization. Imagine a world where data is not standardized and it's just a vague, un-explainable mess! It's a terrifying thought, but fortunately, data standardization is here to save the day and bring order to the chaos. In this blog, I will show you how to create a machine learning program using Python, that does data standardization, and transforms data into a beautifully crafted masterpiece.

Data cleaning, also known as data cleansing or data scrubbing, is a crucial step in the data analysis process. It involves detecting and correcting or removing errors, inconsistencies, and inaccuracies from datasets. Despite its importance, data cleaning can present numerous challenges. For the sake of simplicity, we will assume you are using a language like Python with libraries such as pandas, numpy, and sklearn which are common for data cleaning and preprocessing.