Global Plastic Pollution Analysis with Machine Learning

In the battle against global plastic pollution, data-driven insights are crucial for understanding its extent, identifying hotspots, and devising effective mitigation strategies. Leveraging the power of machine learning, we embark on a journey to analyze and interpret vast datasets related to plastic pollution worldwide. In this article, we explore how machine learning algorithms can uncover valuable insights into the distribution, trends, and environmental impact of plastic pollution...

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Credit Card Fraud Detection | Machine Learning Project

In today's digital era, where financial transactions are predominantly conducted online, the risk of credit card fraud has escalated significantly. According to a report by the Federal Trade Commission (FTC), credit card fraud was the most common type of identity theft reported in 2020, accounting for 39% of all identity theft reports. To combat this growing threat, financial institutions and payment processors are increasingly turning to advanced technologies such as machine learning (ML).

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