Explores the fundamentals of neural networks and their applications in pattern recognition and classification.
Introduction to transformer architectures for NLP tasks like translation, summarization, and Q&A systems.
A study on convolutional neural networks and their impact on modern computer vision applications.
Techniques to make AI models interpretable, ensuring transparency and trustworthiness in AI systems.
Integration of AI algorithms in robotics for navigation, control, and real-time decision-making.
AI-powered diagnostic systems for early disease detection and personalized treatment recommendations.
Efficient frameworks and ML pipelines for processing and analyzing large-scale datasets.
Using NLP and deep learning techniques to determine sentiment polarity in text data.
YOLO and Faster R-CNN models for real-time object detection in images and videos.