Data Analysis:: Performed EDA over Big-Data utilised PowerBI, Tableau Builded Predictive Analytic Models.Created end-to-end products for big insure-tech giants with model accuracy of 90-95 • Data Engineer:: I conducted data scraping and feature engineering to meticulously structure the data, subsequently storing it in a data warehouse. I then conducted SQL query analysis on this well-organized dataset • Full Stack:: Worked on creating Backend Frontend to put a face to product deployed over AWS,Reduced the project maintain cost by using server less tools like Lambda,API-Gateway and other AWS services. Worked upon Node.js and React.js to create the website

Deducted Computational Time : Deducted the computation time for the task of extracting text from unstructured Indian PDF files from 7.8 seconds per/page to 0.1 seconds per/page, about 88 percent reduction • Program Accuracy : Judiciously applied the process of improving accuracy. Previously, the program’s accuracy was 90%; however,As result was able to raise to 98.8%, an increase of the program’s accuracy of about 8.8% • ASI Data : Through advanced analytics, the available ASI Data underwent transformation into both SATA and Nester formats. Clients reported up to 40% enhanced accuracy 20% faster processing times, revolutionizing the data-driven

Dataset Collection: Incorporated robotic sensors (LIS331HH), assisted by a Beaglebone processor. Which helped gather audio data files • Data Generation : Employed data augmentation techniques to produce extra data [4 Times] as amount of data available was essentially nonexistent. slightly altered the data without changing significance and originality • DL Model : With a batch size of 32, Developed a 1D-CNN model that was readily able to reach an accuracy of about 97% in less than 100 epochs