Fake News Detection is a project aimed at using machine learning techniques
to identify and classify fake news articles from genuine ones. The proliferation of misinformation and fake news in the digital age has become a significant challenge, leading to potential
harm to individuals and societies. This project leverages the power of machine learning to help combat this issue and promote reliable information dissemination.
Explore Amazing Mart's Customer Purchase Patterns through an Informative Scatter Plot. Discover Key Insights and Trends to Optimize Marketing Strategies. Uncover Hidden Opportunities for Enhanced Customer Engagement and Business Growth.
Dive into an In-depth Analysis of Customer Bank Usage based on Geographic Regions and Occupations using Tableau. Gain Valuable Insights into Banking Habits, Trends, and Preferences across Different Demographics. Leverage Data-driven Strategies to Improve Customer Services and Drive Financial Growth.
Revolutionizing Healthcare with Advanced Machine Learning: Predicting Diabetes and Averting Its Impact. Harnessing the Power of Data to Identify High-Risk Patients and Enable Proactive Interventions. Empowering Medical Professionals to Deliver Personalized Care and Improve Patient Outcomes.
Decoding what factors influence a candidate's winning chances apart from number of votes with the help of Data Exploration, Visualization, and Statistical Hypothesis Testing using R programming!
Utilizing Python's data manipulation and visualization libraries to perform comprehensive exploratory data analysis on the FIFA 21 dataset, uncovering trends and patterns that offer valuable strategic insights for FIFA enthusiasts
Discovering Customer Insights with SQL: Analyzing Restaurant Data for Valuable Characteristics. Using SQL Queries to Understand Patron Behavior, Preferences, and Trends.
Leveraging Data Findings to Enhance Restaurant Services and Customer Satisfaction.