The main Purpose of Data Cleaning is to identify and remove errors & duplicate data, in order to create a reliable dataset. This improves the quality of the training data for analytics and enables accurate decision-making.

Data cleaning and data preparation is a critical first step in any AI/machine learning project. In reality most data scientists spend most of their time cleaning data during machine learning Project tasks.

In this post we tend to look at some important pandas functions that could assist in data cleaning processes during machine learning tasks.

The first thing we created a sample dataframe for…

Ayanlowo Babatunde

Industrial Engineer with interests in Machine learning/Robotics/IOT