Building Digital Solutions That Matter

A web portal that can monitor the prediction of health diseases can be beneficial for many people to save time by predicting the presence of a disease on their own. These automated services can help physicians in diagnosing diseases.

Created a website that helps patients diagnose the disease by entering their symptoms. I analyzed the datasets for the diseases and preprocessed the datasets that can be used in the model building. I implemented various machine learning algorithms and deep learning algorithms on the datasets.

In this project we are developing an application in which it will allow users to maintain a digital automated diary for expenses. User will login or sign up (for new user) to use this application. Once user has logged in with their credentials they can track their income and expense on a day to day basis.

In recent times, H1B visas have become the most demanded visa. It is a visa that is filed for highly skilled foreign nationals every year. The allocation of these visas is said to be a lottery method which does not rely on any criteria.

The H1B visa application process depends on factors like salary, work location, full-time employment etc. In this project, we are given a data based on the visa applications filed from 2011 to 2016. The baseline models were Naïve Bayes, Random Forest, and XGBoost. Our aim is to outperform their results and train the data on new deep learning models like Neural Networks and Convolutional Neural Networks.

This project is used to analyse and determine sentiment analysis for the dataset using advanced deep learning techniques.