Rajan Dhingra (RajanDhingra)

RajanDhingra

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Location:Singapore

Home Page:rajandhingra.github.io

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Rajan Dhingra's repositories

news_articles_text_mining

The objective of this project is to extract and analyze text data from Medium.

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rajandhingra.github.io

CV Rajan Dhingra

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data_visualisation

The objective of this project is to perform various visulations using ggplot library in R

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web_resys_pred

The objective of this project is to perform web usage mining on an ecommerce dataset called Recsys to identify events that would lead to purchases. This includes creating and testing association rules and sequential patterns in web usage data.

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restaurant_sentiment_analysis

The objective of this train model for positive and negative sentiment based on the star ratings and build classifier

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web_resys_prediction

The objective of this project is to perform web usage mining on an ecommerce dataset called Recsys to identify events that would lead to purchases. This includes creating and testing association rules and sequential patterns in web usage data.

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restaurant_review_sentiment_mining

The objective of this study is to classify the restaurant review as positive or negative. Reviews were scraped from TripAdvisor.

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location_optimisation

. The objective of this research is to identify optimal locations for Sheng Siong, a growing supermarket chain in Singapore. This work focuses on developing models, taking into consideration the various factors that influence the selection of an optimal store location.

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campaign_effectiveness

. This study is of a Portuguese banking institution’s telemarketing campaign wherein our aim is to build a predictive model that will determine the major contributors to customers investing in term-deposits.

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grp_rating_forecasting

The objective of this study is to forecast GRP ratings for Indian Television Channel. Four different forecasting methods were used in this study and the results from each technique were analysed.

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bulk_share_prediction

This work focusses on building single and ensemble models that predict demand for a bike sharing scheme, over a period of 2 years (2011 and 2012) for Capital bikeshare system, Washington D.C.

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