About
Specialties: > Supervised Learning: Linear and logistic regressions, Decision trees, Gradient boosting, Random Forest, Support vector machines (SVM), and Model Evaluation metrics - accuracy, precision, recall, F1-score, and ROC curves. > Unsupervised Learning: k-means clustering, principal component analysis (PCA), Time Series Analysis > Deep Learning: TensorFlow, Keras > Data Analysis Tools: RStudio (caret, factoextra, ggplot, MASS), Python (NumPy, pandas, matplotlib, scikit-learn), MySQL, PyTorch > Methodologies: Git, GitHub
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