End-to-end machine learning and data work: cleaning messy data, feature engineering, training and evaluating models (classification, regression, deep learning, CNNs), and delivering clear, defensible analysis. I benchmark rigorously — my CNN emotion classifier hit 97% accuracy tested against KNN, SVM, MLP, and MobileNetV2. Python, scikit-learn, pandas, NumPy, TensorFlow, PyTorch.