Dinesh Kumar

Architected end-to-end scalable machine learning pipelines, optimizing model training workflows and increasing data throughput by 25%. Deployed interactive Django dashboards to visualize complex analytical insights, reducing administrative reporting latencies by 40%.

Formulated predictive machine learning models for classification and regression tasks, achieving an average validation accuracy of 94%. Executed complete data cleaning, feature engineering, and exploratory data analysis (EDA) using Scikit-learn and Pandas on 10,000+ data records.

Grade: 91%

Pursuing a Bachelor of Technology in Artificial Intelligence & Machine Learning with a current percentage of 91%, expected to complete in 2027.

Grade: 96%

Completed Pre-University Course (Intermediate) with a focus on Mathematics, Physics, and Chemistry, achieving a percentage of 96%.

Grade: 99%

Completed Secondary School Certificate (SSC) with a percentage of 99%.

Professional developer certification for building custom applications and workflows on the ServiceNow platform.

Professional administrator certification validating configuration, management, and operations expertise on the ServiceNow platform.

Completed final project on the GAIA benchmark involving multi-modal agent workflows, tool-calling, and reasoning.

Conducted exploratory data analysis, predictive risk modeling, and collections strategy using generative AI.

Practical machine learning pipelines and deep learning workflows.

Regression, classification, clustering, model evaluation, and Scikit-learn data preprocessing.