Mukut Sharma

Implementation of customized neural network architectures to optimize model performance. Model building for multi-regression problems, specifically adept at handling scenarios with approximately 1000 input variables and 500 output variables. Implementation of machine learning and deep learning models derived from research papers and evaluating the results. Graph data analysis and proficient in evaluating neural network models using diverse graph embedding techniques for enhanced insights and performance optimization.

Worked on challenging fundamental Artificial Intelligence problems in areas of Machine Learning, Deep Learning, Natural Language Processing. Used machine learning tools to select features, create and optimize classifier. Processed, cleaned, and validated the integrity of data to be used for analysis. Written automated scripts to extract data from different sources. Used statistical tools to identify, analyse, and interpret patterns and trends in large data sets that could aid in diagnosis and prediction.

Performed exploratory data analysis to uncover trends, patterns, and insights. Worked on extracting meaningful features from diverse datasets to improve model accuracy. Utilized tools like Matplotlib, Seaborn, or Tableau to present findings in a clear and understandable manner. Documented the entire data science process, including data collection, preprocessing steps, model development, and evaluation metrics. Engaged in mentorship opportunities and seek guidance to enhance skills and knowledge in the field of data science.