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Real-world AI/ML projects with measurable results and business impact
Healthcare Research Project
Manual MRI analysis was time-consuming and prone to human error. Needed an automated system to detect brain tumors with high accuracy.
Developed a CNN-based deep learning model using TensorFlow and Keras. Implemented data augmentation and transfer learning with pre-trained models.
The system can now process MRI scans in seconds, providing doctors with instant preliminary analysis and significantly reducing diagnostic time.
Financial Analytics Startup
Investors needed accurate short-term stock price predictions to make informed trading decisions.
Built LSTM neural network model analyzing historical data, technical indicators, and market sentiment. Created interactive dashboard with real-time predictions.
Users reported 15% improvement in trading decisions and reduced risk through data-driven insights.
Educational Institution
Traditional exam systems lacked personalization and couldn't adapt to student performance in real-time.
Developed adaptive testing platform with AI-driven question selection, automatic grading, and performance analytics.
Teachers saved hours on grading while students received instant feedback and personalized learning recommendations.
SaaS Company
High customer churn rate was impacting revenue. Needed to identify at-risk customers before they cancelled.
Built machine learning model analyzing user behavior, engagement metrics, and support tickets to predict churn probability.
Proactive retention campaigns reduced churn by 25%, saving significant revenue and improving customer lifetime value.
Security & Surveillance
Manual monitoring of security footage was inefficient. Needed automated threat detection system.
Implemented YOLOv8 model for real-time object detection with custom training on security-specific scenarios.
Automated threat detection reduced security personnel workload and improved response time to incidents.
E-commerce Platform
Thousands of customer reviews needed analysis to understand product sentiment and improve offerings.
Built NLP pipeline using BERT for sentiment classification with interactive dashboard showing trends and insights.
Product team identified key improvement areas, leading to 20% increase in positive reviews within 3 months.
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