Shaiknikhat User

I am an entry-level AI/ML engineer with hands-on experience in machine learning, deep learning, and computer vision using Python, TensorFlow, and Scikit-learn. I build real-time solutions for image classification, object detection, and NLP.

During internships and open-source contributions, I developed models for loan-status prediction, job-post classification, and multiple computer-vision projects, and I executed extensive QA testing for web and mobile apps. I reported 50+ critical bugs and designed 100+ manual test cases while collaborating with cross-functional teams.

Notable projects include a 3D object-detection system (R-CNN + YOLO) with 97% detection accuracy, a mask-based student attendance system with 92% accuracy, and a breast-cancer classification pipeline using Vision Transformer and attention mechanisms. I have also improved document classification accuracy to 95% using TF-IDF and Logistic Regression.

I am passionate about building impactful AI applications, contributing to open-source, and continuously improving my skills through certifications and practical projects. I value collaboration, rigorous testing, and delivering deployable ML solutions.