Deeply passionate about Artificial Intelligence and Machine Learning, with a strong interest in exploring algorithmic principles, model development, and real-world applications. Enjoys hands-on implementation—ranging from classical ML methods (e.g., regression, decision trees, SVM) to deep learning architectures (e.g., CNNs, RNNs, Transformers). Actively follows cutting-edge research, especially in large language models, generative AI, and their innovative applications in NLP, computer vision, and beyond. Committed to continuous learning through open-source contributions