Akhila VS

Data Science Intern

Rubixe•  June 2023 - January 2024•  Bangalore

Conducted in-depth exploratory data analysis (EDA) on large datasets to identify key patterns, trends, and correlations. Utilized advanced visualization techniques to present data-driven insights, resulting in improved decision-making. Applied statistical methods and mathematical modeling for data interpretation, including hypothesis testing, regression analysis, and probability distribution fitting, leading to more accurate data insights and predictive models. Engineered and selected features to enhance model accuracy, including creating interaction terms, polynomial features, and one-hot encoding categorical variables. Improved model performance by 15% through refined feature engineering processes. Developed and optimized machine learning models using a variety of supervised and unsupervised algorithms. Achieved up to 90% accuracy on classification tasks using Python. Conducted extensive hyperparameter tuning utilizing RandomizedSearchCV and GridSearchCV to optimize model parameters, resulting in a 10% increase in model accuracy and stability across test datasets. Developed and deployed a Convolutional Neural Network (CNN) for image classification tasks. Implemented data augmentation strategies and K-fold cross-validation to enhance model robustness, achieving 95% accuracy in classifying complex image datasets.