The second session of the Machine Learning Workshop Series organised by the Department of Computer and Data Science concluded as a day full of essential groundwork. This session focused on the critical process of Data Preprocessing—a fundamental step that sets the stage for successful model development.
During the session, NSBM Computing students learned how to load and explore datasets using Pandas in Python, mastered the art of Data Cleaning, including handling missing values and correcting data types, explored techniques for Removing Unnecessary Data and ensuring data consistency, visualized clean data to identify trends and patterns before moving on to model development and worked with Real-World Time Series Data, identifying and selecting the largest continuous section for analysis. They also got hands-on with Python, cleaning and preparing data, and making sure it was ready for the next step in their machine-learning journey.