aviator10 Goto Github PK
Name: NEERAJ SINGH
Type: User
Location: New Delhi, India
NEERAJ SINGH's Projects
analysis-and-prediction-of-online-shoppers-purchasing-intention-using-various-algorithms-capstone
Build a predictive machine learning model that could categorize users as either, revenue generating, and non-revenue generating based on their behavior while navigating a website. In order to predict the purchasing intention of the visitor, aggregated page view data kept track during the visit along with some session is used and user information as input to machine learning algorithms. Oversampling/Undersampling and feature selection techniques are applied to improve the success rates and scalability of the models.
brand-perception-analysis-social-media-analytics-text-mining
Do a brand perception of a Twitter trend by extracting Twitter mentions for the brand and conduct text mining (Correlation, Frequency, Topic Modelling, Sentiment Analysis) on it.
forecast-5-year-souvenir-data-sales
Forecast 5 years sales of souvenir data using Holts-winters and ARIMA methods.
india-credit-risk-default-model
Creating an India credit risk(default) Logistic Regression model
loan-purchase-modelling-therabank
Build a model that will help them identify the potential customers who have a higher probability of purchasing the loan.
predicting-employee-transportmode
Predict whether or not an employee will use Car as a mode of transport from given employee information about their mode of transport as well as their personal and professional details like age, salary, work exp. Also, which variables are a significant predictor behind this decision?
predictive-model-for-choosing-correct-shipping-mode-supply-chain-and-logistic-analytics
Build a predictive model to ascertain the correct shipping mode and choose the significant predictors wisely.
telecom-customer-churn-prediction-assessment
Simulate one case of customer churn where we work on a data of postpaid customers with a contract. Predict whether a customer will cancel their service in the future or not.
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