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https://student-marks-predicting.herokuapp.com/

student-performance-python

A dataset comprising of gender, race/ethnicity, parental level of education, lunch payment method, test preparation course summary of students of a particular college having maths, reading and writing scores on a test.

It consists of 8 columns and 1000 rows.

The notebook contains analysis of how the features are related to each other and the predictive ability of Random Forest Regressor .

Performance of students based on various factors is explored and analysed in the notebook along with correlation between different attributes.

Most asked questions such as is the data biased?, what leads to maximum marks?, most influencing factor? are answered in the notebook.

The model used for deployment is Linear Regression. Yes, you read it right! Linear Regression outperformed other complex algorithms by a considerable margin.

Flask has been used as the framework and the code can be found in the file "app.py" .

HTML files have been stored under the templates folder.

For the visualisation page, sweetviz library of python has been used.

Thankyou!