Designed the architecture and database. Individual contributor for building backend API’s using Django (MVT) involving various data ingestion sources from PowerBI Reports and Snowflake.

Optimized the cost of ETL Transformations from 1425 ETL Jobs to 75 Jobs with auto generation of SQL scripts.

AI powered Diabetic Retinopathy Diagnosis System:

To provide an accurate Diabetic Retinopathy diagnosis result, indicating its level of severity.

Generate a diagnosis report.

Facilitate storing of history and eye scan images

To develop a chatbot which could address the fundamental concerns of users

Machine Learning Model is done with an accuracy 83%.

Deployment of Model into Android Application is completed.

Login and Register for Application

Testing of the result is completed, also generating the Diagnosis report with tested image onto PDF

FAQ (Chatbot) using Dialogflow API

Uploading images option for the user is also completed

Created multiple Intelligent Models which deals with comma-separated value data and obtained different accuracyvalues with respect to each algorithm showing variations.The model is trained with real-life medical records and classified with the disease associated with it.The model intakes the preprocessed data with techniques like Min-Max scalar and one hot encoding.

Market Spend Optimization is a solution that optimizes the expenditure of Business enterprises across all marketingchannels, promotions and digital media marketing.The optimization model takes a huge input of 39 million records of data related to revenue and service spent acrosseach marketing channel with respect to their channels.Exploratory Data Analysis was analyzed with the help of visualization libraries - plotly.express , matplotlib , seaborn.Feature Engineering was implemented with Regression models such as Lasso Regression and weather parameterswere extracted using Visual crossing API with python scripts.The results have been interpreted with a combination of models across several geographies and the estimation ofBudgets to be spent across several marketing channels within the overall budget allocated to the business enterprisewere displayed.

Labor Spend Optimization is an algorithm for optimizing the labors to be allocated on each day/ forth-coming 4-6weeks in each department of the Business enterprise.Labor Spend Optimization includes investigation of data related to Jobs and the capacity of technicians across eachtenant with respect to their geography. The pattern of revenue generation through these jobs and insights about thebusiness are observed across each year.The Optimization model takes a huge input of 30 million records of data related to Jobs, technicians and revenue acrosseach service and geography.Implemented Forecasting models using Time- Series forecasting and experimented on most used Time-series modelslike ARIMA, auto - ARIMA, SARIMAX , and other deep learning techniques like Prophet.

Diabetic Retinopathy is a Flutter application designed to detect the severity of Diabetic retinopathy by taking the retinalimage of an eye, using CNN algorithm, libraries such as OpenCv, Tensorflow 2.0, Tensorflow lite API and G-Firebase asthe database.The model intakes a huge dataset comprising of 80,000 images processed with OpenCv Preprocessing techniques likeEdge Detection, Gaussian blur and several other techniques.The model is deployed onto the flutter environment and provides an attractive and understandable GUI to users.Featured with a Helpdesk screen associated with Diaglowflow API, and also a screen for tracking the history of testsperformed in the Mobile Application.

An e-commerce store android application built using My-SQL database and spring boot as the framework to control allthe operations between the database and Client-side to server-side operations. Built microservices for each of thefunctionality and deployed them into android.

Designed a management system application includes immense work of relational database management system with the help of Nodejs and express libraries to support in the backend.