BCA, NORTH LAKHIMPUR COLLEGE (AUTONOMOUS), NORTH LAKHIMPUR
COMPUTER SCIENCE
JUN. 2018
AVERAGE CGPA - 7.38
HS, REVEREND WILLIAM WARD JUNIOR COLLEGE, NORTH LAKHIMPUR
12th AHSEC, SCIENCE (PCM)
APR. 2014
PERCENTAGE - 62.00%
HSLC, LALUK HIGHER SECONDARY SCHOOL, LALUK
10th SEBA
APR. 2012
PERCENTAGE - 64.00%
Portfolio
MY PROJECTS
Traffic Sign Recognition System
(Deep Learning Project)
Aim of this project is to build a neural network (CNN) model that can classify traffic signs present in the image into different categories.
With this model, we will be able to read and understand traffic signs in real time which are a very important task for all autonomous vehicles
The various Technologies used are:
FrontEnd - Tkinter,
Model - Convolutional Neural Network
Banking Customer and Loan Prediction System is a system that can be used by bank employee to verify with the previous loan applicants data and whether the application was approved or not for the current customer.
In this project , we will build a machine learning model to predict the loan approval probability.
The various Technologies used are:
House Price Prediction system is a software that can be used by Real Estate Business Team to predict
house price. It can be usefull for gaining profit.
The various Technologies used are:
Medical Insurance Cost Prediction is a system that can be used by insurance company to verify with the applicants data and whether the insurance amount is
acceptable or not.
In this project , we will build a machine learning model to predict the insurance amount for the particular applicants.
The various Technologies used are:
Heart Disease Prediction System is a system that can be used by medical departments to verify with the patients data and whether the patients has
Heart Disease or not.
In this project , we will build a machine learning model to predict the Heart Disease probability.
The various Technologies used are:
Diabetes Prediction System is a system that can be used by medical departments to verify with the patients data and whether the patients has
Heart Disease or not.
In this project , we will build a machine learning model to predict the Diabetes probability.
The various Technologies used are: