Vedanta Banerjee.
Digital Craftsman ( Engineer / Developer / Musician )
Hi, I am vedanta, a software programmer, electronics engineer and tech enthusiast trying to turn challenges into innovative solutions with a touch of creativity and a dash of fun!
About Me
Thanks for stopping by! I am an electronics engineer, software developer and a philomath from India. Academically, currently pursuing undergraduate degree in electronics and instrumentation engineering. I am deeply passionate about computers (both hardware and software), space (cosmology), books and music! I like creating digital solutions that make a real impact - brings me joy!
When I am not fixing bugs or tinkering with electronics, you might find me indulging in my love for music, hanging out with my camera and guitar, or diving into a good book. The goal is to have fun while practicing the art of making for betterment of the world.
Education
Bachelor of Technology (B.Tech) in Applied Electronics and Instrumentation Engineering - Heritage Institute of Technology, Kolkata
Latest Experience
Full-Stack Software Engineering Intern at Alchemyst AI
Latest Certifications
• Python for Data Science and Machine Learning Bootcamp [Udemy Certificate]
Latest Achievements
Won $1000 as 1st runner up in the Web3 & AI Hackathon by Encode Club.
My Skills
Frontend
HTML, CSS, React, Next
Backend
JavaScript, Node.js, Python
Databases
mySQL, MongoDB
Cloud
AWS,Vercel
My Development Projects
My AI & ML Projects
CIFAR-10 Image Classification using Convolutional Neural Networks (CNNs)
This project aims to develop a model that can classify images from the CIFAR-10 dataset into one of ten categories. Using convolutional neural networks (CNNs), we will explore the dataset, preprocess the data, train the model, and evaluate its performance.
More detailed information can be found in the GitHub repository:
Car Purchase Amount Prediction using Artificial Neural Networks (ANNs)
An artificial neural network model used to predict the amount a customer is willing to spend on a car based on different factors/features of the customer. This model achieved an R2 score of 0.9892339 and can help car salesmen better understand their customers.
More detailed information can be found in the GitHub repository:
Prediction of customer behavior about paying back lended funds on parameters using Machine Learning
This is a Financial Analysis project that aims to predict whether a new customer will pay back the loan or not based on certain parameters using Decision Trees and Random Forest.
More detailed information can be found in the GitHub repository: