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Disha Sinha's Projects

algo_ds_notes icon algo_ds_notes

It is a repository that is a collection of algorithms and data structures with implementation in various languages.

customer-churn-analysis icon customer-churn-analysis

Implementation of Decision Tree Classifier and Clustering models(Kmodes & Kprototypes) for Customer attrition analysis of bank to identify the cause and conditions of the churn.

employee-salary-prediction icon employee-salary-prediction

A project to Predict salary of employees using Linear Regression & display the results in GUI using Tkinter Module of Python

movie-recommendation-system icon movie-recommendation-system

A recommendation model which finds popular movies according to votes and ratings given to each movie, recommends movies to the user according to the user's previous interactions using K-means Clustering and cosine similarity and also suggests movies to the user based on the likes of similar other users in the dataset using Pearson similarity index.

musical-keyboard icon musical-keyboard

A web application to play music using letters from the keyboard of your PC. Enter letters of your choice and ENJOY;)

resizable-pagination-in-mern icon resizable-pagination-in-mern

Uploaded the Netflix_titles.csv dataset in MongoDB and fetched the data from the server-side to the client side. The dataset has 7767 rows which is huge for a single page. So implemented the concept of resizable pagination in react. The rows can also be selected and deselected using checkbox.

sentimental-analysis-movie-reviews icon sentimental-analysis-movie-reviews

This model performs feature-extraction on the given dataset on the basis of polarity, wordclouds and by removing non-essential words, next it builds a vectorizer which turns the list of words into an array of numbers and then it classifies the reviews into negative or positive based on the keywords of the review.

undernsembled icon undernsembled

In this project, we reduced an imbalanced dataset to a balanced dataset using Under-sampling approach by applying Consensus Clustering using 'Simple Majority Voting' consensus function and further saw the increase in the accuracy of disease prediction by running multiple classifiers with bagging and boosting technique.

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