Shruti Balan's repositories
E-commerce-Customer-Churn-Prediction
This is an end-to-end ML project, which aims at developing a classification model for predicting if a customer for an ecommerce business will churn or not in the following month
Bangalore-House-Price-Prediction
An end-to-end regression problem of predicting the price of properties in Bangalore.
Credit-Card-Default-Predictor
This is an end-to-end ML project, which aims at developing a classification model for the problem of predicting credit card frauds using a given labeled dataset. The classifier used for this project is RandomForestClassifier. Deployed in Heroku.
Fake-News-Detection
A simple end-to-end project on fake v/s real news detection/classification.
South-German-Credit-Risk-Classification
This is an end-to-end ML project, which aims at developing a classification model for the problem of classifying a given customer profile into either of the risk category (Good or Bad). The final classifier used for this project is XGBoost classifier. Deployed in Heroku.
Spam-or-Ham-Detection
Web-api deployed in heroku for predicting if a given message is spam or not.
Retail-Store-Customer-Segment-and-Sales-Analysis
This project looks at the sales pattern of a product category in a retail store, using the store’s transaction dataset and identifying customer purchase behavior, to generate insights and recommendations.
Stock-Sentiment-Analysis
Objective of this project is to predict the increase or decrease in stock market prices, based on the sentiments extracted from news headlines.
Diabetes-Prediction
A classification problem to predict if a patient is suffering from diabetes or not.
Product-Recommender-System-
A simple product recommender using collaborative filtering
python-flask-docker-sample
Sample Python Flask application Dockerized
Store-Sale-Prediction
An end-to-end ML project, which aims at developing a regression model for the problem of predicting the sales of a given product, based on its properties like item category, weight, visibility, MRP, type of outlet the product is sold, size of the outlet etc.