Machine learning I can clean and manipulate data sets as well as do statistical analysis and visualization. The core hard-skills in day-to-day work: Probability and Statistics: explore and understand more about the data, identify the underlying relationships, predict future trends, determine patterns, uncover anomalie Calculus and Linear Algebra: derivatives and gradients, step function, sigmoid function, logit function, ReLU (Rectified Linear Unit) function, cost function, plotting of functions, minimum and maximum values of a function, scalar, vector, matrix and tensor functions Programming, Packages and Softwares: Python, SQL, Julia, TensorFlow Data Visualization: plot data, determine relationships between variables, visualize areas that need attention, display trends, connections, visualize volume of information, client reporting Machine Learning / Deep Learning: K-nearest neighbors, Random Forests, Naive Bayes, Regression Models, SVM, Scikit-Learn, XGBoost, PyTorch, TensorFlow, Keras, Time series, Natural language processing, Outlier detection, Computer vision, Recommendation engines, Survival analysis, Reinforcement learning, Adversarial learning.