Student's Grades Assessment

• Pre-Processed the data using various data imputation and balancing methods and uploaded the data in Azure Blobs.
• Built Prediction model using Decision Forest (Over Sampled) on azure ML with 90% accuracy after comparing its metrics with Neural networks, Two class SVM, Naïve Bayes and Logistic Regression in Python.
• Performed classification using SVM Model (Over Sampled) on azure ML with 78% accuracy after comparing its metrics with Neural networks, SVM, Naïve Bayes and Logistic Regression in Python.
• Developed a Python Flask Application and deployed the classification and prediction model on Google Cloud.
• Technologies used: Python, Azure ML, Flask, Google Cloud Platform.

For Demo:

• https://youtu.be/n19w2lbwduM