Anitha Rajeswari

Successfully developed a machine learning model as part of a professional team. Contributed to tasks related to machine learning projects within a collaborative environment. Analyzed data and collaborated with team members to optimize algorithms for model development. Improved model performance through hyperparameter tuning, reducing training time and enhancing accuracy. Implemented advanced algorithms and feature engineering techniques to further increase model accuracy. Optimized models through hyperparameter tuning and feature engineering, significantly reducing training time and improving overall accuracy.

Mentored students and communicated internship and employment opportunities. Spearheaded operations in the Microprocessor Lab, while instructing a VLSI Design theory course. Administered exam duties for semester students, ensuring adherence to academic standards and guidelines. Developed materials and exercises to effectively illustrate and apply course concepts.

Taught mathematics to students across various grade levels, ensuring comprehensive understanding of key concepts. Developed and implemented lesson plans tailored to the individual needs and learning styles of students. Fostered a positive learning environment, encouraging critical thinking and problem-solving skills. Prepared students for academic assessments, resulting in improved performance in mathematics. Collaborated with colleagues to integrate interdisciplinary approaches and enhance overall curriculum effectiveness.

Developed a machine learning model to predict the salary of newly hired employees using company data. Analyzed and preprocessed the dataset to ensure accuracy and relevance. Implemented multiple regression models and evaluated performance using metrics such as R-squared and MAE. Optimized the model to enhance predictive accuracy. Proficient in Python, Pandas, Scikit-learn, and Jupyter Notebook online.

Participated in multiple industrial visits and national paper conferences to enhance technical knowledge and practical skills.

Project: Developed a MATLAB-based project to predict image quality using the PSNR (Peak Signal-to-Noise Ratio) method, improving image analysis and quality assessment.

Completed a comprehensive course covering Python from basic to advanced levels. Gained hands-on experience in: Python Fundamentals: Variables, loops, conditionals, and functions.