In my current role, I focus on minimizing food waste by predicting attendance rates for events and services. By analyzing historical data and forecasting attendee numbers, I help organizations send the right amount of food, thereby reducing excess and promoting sustainability.In addition to my work in food waste reduction, I have extensive experience in financial data analysis. I provide actionable insights that aid in strategic decision-making and enhance overall financial efficiency.

"Possibilities and limitations for AI-related edge computing on a Raspberry Pi"

"Pattern Recognition In Electrical Consumption For Online Load Monitoring Using Smart Meters"By monitoring water and electricity consumption to identify which appliance is running by using machine learning with some a-priori pattern information.

Ubiqum code academy is an intensive programming course.- 800 + hours of onsite full-time coding training- “Learning by doing” with real data and projects using SQL and R- Agile Methodology- Time Series Analysis (forecast & visualization) with energy consumption data- Supervised Machine Learning for sales volume prediction, brand preference prediction and a Wifi positioning system (Classification & Regression with KNN, RF, SVM, GBM)- Market basket analysis (apriori algorithm, recommender systems)- Big Data Analytics and Cloud Computing with AWS

▪ Giving Direction to Field Engineer to install Wimax CPE installation at the client end.▪ Troubleshoot and maintenance.▪ Drive test for checking coverage area.▪ Measuring the BTS coverage area and locating client end by Google Earth.▪ Coordinating as an Installation Supervisor and providing feedback on radio status, ping test.