Profile Picture

Shreyansh Soni

Shreyansh Soni

A

A Developer

A Developer

An aspiring young engineer with experience in various fields such as : Machine Learning, Data Structure and Algorithm, Designing UI/UX and IoT. I have worked for various societies and workplaces in different areas to develop a broad skill set.

I am currently working on a project to device a novel method to remove Salt and Pepper noise from images taking less time than the conventional, already present algorithms.

#savvy #motivated #communicative #hard-working #cool-headed #organized #easy-going

< Skills >

#Organization #TimeManagement #Communication

< Education >

Graduation
2018-2022

Thapar University

BE in Electronics and Communication

Class 12
2016-2018

St.Anselm's Pink City School

81% in PCM CBSE Board

Class 10
2016

St.Anselm's Pink City School

91% CBSE Board

< Projects >

Brain Tumor Detector

Image Noise Remover and Tumor Detector

A project which removes SAP noise from fMRIs and detects Brain Tumor with accuracy percentage.

Accomplishments
  • Tools: MATLAB, Convulated Neural Networks, MyHDL
  • We use a Novel technique to remove Salt and Pepper Noise from the Image.
  • Our technique involves a Dynamically Adjustable Switching Based Median Mean Filter
  • The then noise free Image is fed to a pre trained Neural Network Model.
  • Which detects whether there is any tumor and what kind of tumor it is.
Water Management

Smart Domestic Water Management System

A project using IoT devices for Smart Water Management in Domestic Buidings.

Accomplishments
  • Tools: Blynk, ESP32 Controller, Flow Meter, pH Sensor, TDS sesnor
  • A full fledged system to ensure a seamless supply of water in high rise building societies.
  • It utilises various sensors and IoT devices along with an App and Web UI to keep tarck of all activities
  • Along with this the system also takes various steps to reduce water wastage and methods to save water.
  • The cost of the entire system is also a kept a key factor while designing the whole system.
Brain Tumor Detector

Loan Predictor using various models of ML

A project that predicts whether a given client will be granted loan or not using ML models.

Accomplishments
  • Tools: Jupyter Notebook, NumPy, Pandas, Logistic Regression, XG Boost, Random Forest
  • We use the ability of libraries such as Pandas and NumPy to create and feed the database of customers to the system.
  • After that we train our model using different models such as Logistic Regression, XG Boost, Random Forest
  • We find the model with best accuracy rate with the test data and with a better model we are able to predict the loan status of clients with maximum accuracy.

< Contact >