From Text To Tables: Why Structured Data Is AI’s Next $600B Frontier

Tabular foundation models are the next major unlock for AI adoption, especially in industries sitting on massive databases of ...
IEEE

Data-Driven Solutions for Human Trafficking: Detection and Impact Analysis Using Machine Learning

Abstract: Human trafficking is a serious problem that requires new ideas and data-driven approaches to identify and solve. In this study, we analyze large datasets to identify patterns and anomalies ...
IEEE

Imbalanced Data Problem in Machine Learning: A Review

Abstract: One of the prominent challenges encountered in real-world data is an imbalance, characterized by unequal distribution of observations across different target classes, which complicates ...
IEEE

Enhancing Customer Retention: A Federated Machine Learning Framework for Banking Churn Prediction

Abstract: Customer attrition has become the significant challenge for the bank, making large volume of customers to migrate to other banks, as the banks keeps providing multiple benefits to the ...
IEEE

Forest Fire Forecasting Leveraging Modis Satellite Fire Data Using Machine Learning For Jharkhand State, India

Abstract: Forest fires pose significant environmental and economic threats, necessitating robust predictive models for better management and prevention. This study focuses on the temporal and spatial ...
IEEE

Enhancing Nucleus and Cytoplasm Segmentation in Cervical Cytology Using Deep Learning

Abstract: Cervical cancer, with over 660,000 cases in 2022, ranks as the fourth most frequent malignancy in women globally, with low- and middle-income nations accounting for approximately 94% of the ...
IEEE

Analyzing Customer Feedback on Amazon to Reveal Sentiment Trends using Machine Learning

Abstract: Online reviews on platforms like Amazon provide valuable insights into customer experiences, but manually processing this data is time-consuming and impractical. This paper “Analyzing ...
IEEE

Harnessing Machine Learning for Effective Customer Segmentation

Abstract: The paper’s objective is to utilize machine learning techniques for customer segmentation. We aim to identify significant patterns and segments within a customer base to enhance marketing ...
IEEE

Optimizing Customer Satisfaction Through Sentiment Analysis: A BERT-Based Machine Learning Approach to Extract Insights

Abstract: In the era of digital transformation, customer feedback has become crucial for improving service quality. This study aims to enhance customer satisfaction through sentiment analysis ...
IEEE

Customer Segmentation using Mini Batch K-Means Clustering Algorithm

Abstract: Today, especially in this era of data, everything is becoming more mechanized. Data is the new electricity of the globe. This knowledge may help a lot of businesses in their marketing ...
IEEE

Machine Learning Insights for Predicting Customer Behavior in Online Retail

Abstract: The research work reports a comprehensive analysis of predictive analytics of customer behavior on e-commerce based on high-end data science and artificial intelligence techniques. The ...
IEEE

Efficient Machine Learning-Based Semantic Segmentation Algorithm for Consumer-Grade AAV Remote Sensing

Abstract: The computational complexity of the Transformer model grows quadratically with input sequence length. This causes a sharp increase in computational cost and memory consumption for ...