Conducted comprehensive sensory evaluations of wines, leveraging industry-standard techniques and protocols to objectively assess and describe the wines.Utilized advanced analytical methods to measure and interpret key chemical components of the wines, such as alcohol content, acidity, tannins, and other factors.Implemented various data preprocessing techniques, including feature engineering, encoding, and outlier detection, to enhance the predictive performance of the regression models.Acheived a robust and scalable data processing pipeline, integrating state-of-the-art machine learning libraries and frameworks, to streamline the wine testing workflow.Demonstrated proficiency in utilizing a wide range of industry-standard tools and software, such as Numpy, Pandas, Scikit-learn,Seaborn and Matplotlib, to conduct data analysis, model development, and visualization tasks.