Bhavadip Dobariya

Topic: Process Prediction in warehouses • created a dataset by performing video annotations task of 1.6 million frames with an accuracy of 95.89% • Reduced model training time by 20% through effective data cleaning and preprocessing using Numpy and Pandas • Implemented machine learning models: Supervised and Unsupervised Hidden Markov Models • Visualized the predictions using Python libraries: Matplotlib and Seaborn • Achieved the 92.47 % precision in predictions

Topic: Traffic Data Analysis and Route Optimization • Extracted OpenStreetMap data using Python library OSMnx • Performed data cleaning and preprocessing with Numpy and Pandas • Developed a dynamic weight function considering traffic, signal wait times, road types, and some other key factors • Conducted traffic analysis and optimized route planning based on start and destination points

• Automated the automotive sales data extraction process by using SQL stored procedures • Analyzed sales trends and customer behavior by using SQL queries • Visualized Ad-hoc reporting through interactive dashboards in Power BI • Communicated with senior sales and marketing team members to enable data- driven decision-making

• Automated the automotive sales data extraction process by using SQL stored procedures • Analyzed sales trends and customer behavior by using SQL queries • Visualized Ad-hoc reporting through interactive dashboards in Power BI • Communicated with senior sales and marketing team members to enable data- driven decision-making