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ImageI am a highly motivated computer science student with hands-on experience in AI/ML workflows, data preprocessing, and model evaluation through my AWS Academy AI/ML Virtual Internship. My background includes working with real-world datasets, handling data cleaning and normalization, and building robust preprocessing pipelines for deep learning models, such as my project on turbofan engine RUL prediction using advanced architectures like DenseNet-1D and Bi-LSTM with Attention. I am skilled in Python, Pandas, NumPy, and scikit-learn, and have a solid understanding of cloud-based data handling using AWS services. I am eager to apply my analytical skills and attention to detail to data labeling and annotation tasks, ensuring high-quality training data for AI systems.
Training and labelling both images and csv datatype format datasets to train a ML model for classifying into stress and depression classes..
Bachelor of Technology, Computer Science and Engineering
Higher Secondary Certificate, Science
AI/ML Intern
