Skip to content
Students Performance Evaluation using Feature Engineering, Feature Extraction, Manipulation of Data, Data Analysis, Data Visualization and at lat applying Classification Algorithms from Machine Learning to Separate Students with different grades
Jupyter Notebook
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
.github/ISSUE_TEMPLATE
.gitignore
CODE_OF_CONDUCT.md
CONTRIBUTING.md
LICENSE
README.md
Student_Performance.ipynb
StudentsPerformance.csv
analyzing-students-performances.ipynb
pull_request_template.md

README.md

Student-s-Performance-Analytics

Students Performance Evaluation using Feature Engineering, Feature Extraction, Manipulation of Data, Data Analysis, Data Visualization and at lat applying Classification Algorithms from Machine Learning to Separate Students with different grades

Description

Context

Marks secured by the students in different subjects like

  1. Maths
  2. English
  3. Science with some other important credentials related to academics

Content

This data set consists of the marks secured by the students in various subjects.

Acknowledgements

http://roycekimmons.com/tools/generated_data/exams

Inspiration

To understand the influence of the parents background, test preparation etc on students performance

You can’t perform that action at this time.