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Great Learning brings you this live session on "Machine Learning Project on Student grade Prediction". In this session, you will be working on an end-to-end case study to understand the different stages of Model building using the Machine Learning concept. This will deal with "data manipulation" with pandas and Numpy, and "data visualization" with Matplotlib and Seaborn libraries with the Student grade dataset. After Data manipulation and Data visualization, Exploratory data analysis will be performed on the Student grade and then an ML model will be built on the student grade dataset to create a model/system which can predict the grade according to the different attributes. You will also learn about the basics of the sci-kit-learn library to implement the machine learning algorithm.
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