As a long-time practitioner in Machine Learning engineering, statistical analysis is my bread and butter, excelling in data mining and utilizing the R programming language to mine and structure data sets for optimal analysis. I'm proud to say that I've built applications in MATLAB and Excel for over a decade, paving the road for me to become skilled in optimization, numerical analysis, statistical analysis as well as offering support for Relevant and understandably, my skill set developed around these areas covers race data management, evaluation of horse's performance using historical data for race predictions, analysis of various track conditions, and studies on jockey/trainer statistics.
Continuously seeking self-improvement, I've delved into Machining Learning techniques: supervised and unsupervised algorithms such as SVM, Naive Bayes, Nearest Neighbor, K-means clustering. Combining these skills with statistical knowledge like descriptive statistics, regression analysis and hypothesis testing acquired through rigorous academic training ensures an evidence-based approach to my work.