This is a basic student performance analysis with predefined data using basics of machine learning. We used a predetermined dataset consisting of students marksheets. The output analysis is visualized using graphs for each subject and its chapters. It is done using K-Clustering algorithom which is an unsupervised learning algorithm. Here a subject mark's labels are grouped into one single cluster. This helps to analyse the student's performance and help him do better in upcoming exams
Libraries Used
We have used the below libraries to implement data analysis and to visualise student's data
Python 22621 Version:1.24.1
Python 22621 Version:1.24.1 License: Permissive (BSD-3-Clause)
Python 22452 Version:1.16.0
Python 22452 Version:1.16.0 License: Permissive (Apache-2.0)
Python 36783 Version:1.5.2
Python 36783 Version:1.5.2 License: Permissive (BSD-3-Clause)
Python 16825 Version:3.6.2
Python 16825 Version:3.6.2 License: No License
Python 18029 Version:2.7.1
Python 18029 Version:2.7.1 License: Permissive (MIT)
Python 15677 Version:8.8.0
Python 15677 Version:8.8.0 License: Permissive (BSD-3-Clause)
Python 0 Version:Current
Python 0 Version:Current License: No License
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