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IEEE-style report on sentiment analysis of Twitter tweets using the Sentiment140 dataset. This project involves data cleaning, preprocessing, and applying machine learning techniques to classify tweets as positive or negative. The report follows IEEE format and includes detailed analysis, methodology, and evaluation of the models used.

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About Section

This repository contains the LaTeX code for the final report of an applied machine learning project that performs sentiment analysis on the Sentiment140 dataset.

The project utilizes various data cleaning techniques and classification models, such as Logistic Regression and Support Vector Machines (SVM), to analyze public sentiment in Twitter data.

The dataset consists of 1.6 million labeled tweets, and the report includes an in-depth exploration of the dataset, the preprocessing steps taken, the models applied, and the evaluation results.

The code repository can be found here: [https://github.com/adhillon192/SimpleMLProject]

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IEEE-style report on sentiment analysis of Twitter tweets using the Sentiment140 dataset. This project involves data cleaning, preprocessing, and applying machine learning techniques to classify tweets as positive or negative. The report follows IEEE format and includes detailed analysis, methodology, and evaluation of the models used.

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