Gaining expertise in managing data and extracting relevant information from it.
Skills: Languages and Databases: Python, R, SAS, MySQL
Data Science Tools: Tableau, Pandas, NumPy, OpenCV, TensorFlow, PowerBi
Software packages: MS Office (MS Excel, MS Presentations, MS Word), Enginius, Mimic Pro
Modeling Techniques: Decision Trees, Random Forests, Linear & Logistic Regression, SVM, KNN, PCA, Naïve Bayes, Gradient Boosting, XgBoost, Neural Networks, Regularization, Cross-validation, Clustering, Time Series, NLP.