Project P05: Want to predict your result?

Mentor: Chirag Sharma

Details

This is a project from scratch to intermediate level for prediction of marks. Working through data by cleaning and arranging and then visualize and analyze it to predict the marks for next semester. Working through different algorithms to find which is better and why?

Tech Stack:

1. Python (Data Cleaning, Analysis, and Visualization),
2. Jupyter Notebook,
3. Machine Learning

Road Map

• Using pyPDF2 and Regular Expressions to Clean Data (1 Day)
• Pandas, Matplotlib and Seaborn to analyze, visualize data (1-2 Day)
• Concepts of Statistics such as mean, variance,standard deviation and likelihood covered (1 Day)
• Using Linear Regression, K-Nearest Neighbour and Random Forest to predict marks with very high accuracy. (1-2 Day)

Resources

• DataSets: https://github.com/iamchiragsharma/resultAnalytics/tree/master/pdfs
• Github Repo(All Resources): https://github.com/iamchiragsharma/resultAnalytics
• Statistics: https://www.youtube.com/watch?v=qBigTkBLU6g&list=PLblh5JKOoLUK0FLuzwntyYI10UQFUhsY9
• Machine Learning: https://www.youtube.com/watch?v=Gv9_4yMHFhI&list=PLblh5JKOoLUICTaGLRoHQDuF_7q2GfuJF