Anchal Gupta

Developed a music recommender system in Python using hybrid recommendation technique.
 It recommends songs based on content such as artist, genre, user behavior & similarity such as age, gender and demography.

Sentiment Analysis of tweets about Delta Airlines, Alaska Airlines and United Airlines using text mining techniques such as sentiment analysis and clustering.

Developed a classification model for predicting whether a person may have a heart disease or not.
 Developed an ensemble model of 4 different classification algorithms –
1. SVM
2. Neural Network
3. Decision Tree
4. Logistic Regression.
 Achieved the model accuracy of 97.5%.

Developed a classification model for predicting whether a subscriber will churn from a telecom service provider using classification algorithms- Decision Trees & Neural Networks.
 Validated the model using k-fold cross validation.
 Predicted the customer churn with 92% accuracy.

Identified the optimal warehouse from a list of potential warehouses which could cover maximum zip codes using 2-day shipping with minimum cost.
 Developed regression model to analyze the relationship between distance from warehouse to customer, delivery duration and cost.
 Used linear programming for identifying the optimal warehouse location based on distance between the warehouse and the zip codes in the seller’s distribution profile.