AI annotator
Classifying various photos across a range of topics from people to locations around the world.
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I am passionate about AI and machine learning, with hands-on experience in data annotation, model evaluation, and training data preparation across NLP and computer vision domains. My work includes fine-tuning large language models for contextual semantic understanding, evaluating model outputs using cognitive task analysis, and developing CNN-based classifiers for deepfake detection with interpretability techniques like Grad-CAM. I have built ensemble models for behavioral analytics and churn prediction, applying feature engineering and statistical analysis to optimize data-driven insights. My technical toolkit spans Python, TensorFlow, PyTorch, Scikit-learn, XGBoost, and SQL, and I am skilled in leveraging tools such as Streamlit and Plotly for data visualization. I am committed to ensuring high-quality, robust AI systems by focusing on accurate data labeling, model transparency, and actionable insights.
Classifying various photos across a range of topics from people to locations around the world.
Minor, Artificial Intelligence and Machine Learning
Bachelor of Technology, Electronics and Communication Engineering
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