SKILLS
Programming and Tools: Python | NumPy | pandas | matplotlib | seaborn | scikit-learn | SQL | TensorFlow | Spark and PySpark | Git | GitHub.
Data Analysis and Statistics: Data Analysis | Statistics and Probabilities | Probability distribution.
Machine Learning and Data Science: Data Preprocessing (handling missing data, encoding categorical data, feature scaling), Regression (Simple Linear Regression, Multiple Linear Regression, Polynomial Regression, Support Vector Regression (SVR), Decision Tree Regression, Random Forest Regression), Classification (Logistic Regression, K-Nearest Neighbors (K-NN), Support Vector Machine (SVM), Kernel SVM, Naive Bayes, Decision Tree Classification, Random Forest Classification), Clustering (K-Means, Hierarchical Clustering), Association Rule Learning (Apriori, Eclat), Reinforcement Learning (Upper Confidence Bound (UCB), Thompson Sampling), Natural Language Processing, Deep Learning (Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN)), Dimensionality Reduction (Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), Kernel PCA), Model Selection & Boosting (k-fold Cross Validation, Parameter Tuning, Grid Search, XGBoost).
Soft Skills: Active listening | Effective communication | Sharing feedback | Attention to detail | Leadership | Empathy. Business Applications: Predictive Modeling, Forecasting, Financial Analysis, Healthcare Analytics
Languages
English (Fluent)
Spanish (Native)
