Welcome to my GitHub repository showcasing a significant project I undertook during my Bachelor's program in Data Science. In the following sections, I'll provide an overview of the project and its objectives, as well as the methodologies and insights gained.
As part of the "Hands-On Machine Learning and Data Science" university course, I dedicated a semester to delve into a crucial topic in the realm of data science: the identification of fake news through textual analysis. Leveraging my skills and knowledge, I embarked on a comprehensive exploration of various algorithms and techniques to achieve accurate and insightful results.
This repository contains the Jupyter Notebook detailing the entire project, capturing the journey from data collection and preprocessing to model selection and evaluation. Here's a deeper look into the key components:
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Data Collection: Describing the data sources and methods used to curate a relevant and diverse dataset for training and testing.
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Data Preprocessing: A pivotal phase of the project, I invested significant effort in preprocessing the data. This involved text cleaning, tokenization, handling missing values, and feature engineering. Ensuring high-quality data was essential to developing a robust and accurate fake news detection algorithm.
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Algorithm Comparison: One of the project's cornerstones, I conducted an in-depth comparison of various machine learning algorithms. This included Logistic Regression, Random Forest, and potentially others. By meticulously evaluating their performance and nuances, I gained insights into which approaches were most effective for the task.
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Impact of Data Variation: I explored the effects of introducing minor variations in training data. This investigation shed light on the algorithms' sensitivity to data changes and provided insights into their adaptability and generalization.
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Title Influence: An intriguing aspect of the project was the examination of whether the article's title significantly influenced the accuracy of fake news detection models. This exploration added a unique dimension to the analysis.
The ability to identify fake news is becoming increasingly important in today's digital age. This project showcases not only my technical skills in data preprocessing, machine learning algorithms, and data analysis but also my dedication to tackling real-world challenges through innovative solutions.
Thank you for taking the time to explore this project. Your interest is greatly appreciated.