Projects
Project 1: Sentiment Analysis on Twitter Data
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As a passionate data science enthusiast, I have developed a project on sentiment analysis using Python's Natural Language Toolkit (NLTK) and Twitter API.
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The goal was to analyze the sentiment of tweets and identify whether they are positive, negative or neutral.
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The project involved scraping tweets using Twitter API, preprocessing the data, and using NLTK to perform sentiment analysis.
Project 2: Predicting Customer Churn with Machine Learning
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In this project, I built a machine learning model to predict the customer churn of a telecommunications company.
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I used Python's Scikit-Learn library to train and test the model on a dataset of customer information, such as their usage patterns, demographic data, and service details.
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The model achieved an accuracy of 85%, which helped the company to identify the customers who are likely to churn and take proactive measures to retain them.
Project 3: Visualizing Real-time Stock Market Data with Tableau
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I have also developed a project on visualizing real-time stock market data using Tableau.
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The project involved extracting real-time data from Yahoo Finance API, cleaning and preprocessing the data, and creating interactive visualizations that can help investors to make informed decisions.
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The project showcases my skills in data visualization, data preprocessing, and Tableau.
