Data preprocessing is an important step to prepare the data to form a Machine Learning model. There are many important steps in data preprocessing, such as data cleaning, data transformation, and feature selection. Data cleaning and transformation are methods used to remove outliers and standardize the data so that they take a form that can be easily used to create a model.
Join us this Saturday 14th November, we will be talking about data preprocessing in depth and we will be handling a raw data to get it ready for processing.
DSC ENSAM Casablanca Lead