kunalsingh-physics Goto Github PK

bose-einstein-condensate-bec-in-harmonic-trap

Various models have been developed to calculate the ground state wavefunction of BEC. The Gross Pitaevskii equation models the ground stave wave function of the interacting system of Bosons at temperature T=0K. In this project, we solve the Time-dependent Gross-Pitaevskii equation using Crank Nicholson Finite Difference method using Python. The res

closed-box-galactic-evolution-model

cnn_cats_and_dogs

A basic CNN image classification model which can classify images of dogs and cats

counting-stars-in-an-image

A simple python program which counts stars in a program we use simple image thresholding to seperate the objects from the background.

crossmatching-astronomical-data

Cross-matching is an important tool in astronomy data analysis. This project aims to design a program to cross match two data catalogues and improve the time complexity. We cross-matched AT20G with SuperCOSMOS, AT20G with SDSS and BSS with SuperCOSMOS.

denoise_audio

A simple program that can denoise audio signals. This Program was written by Kunal Singh, Vidhi Tailor and Nilay Ghalsasi of St. Xaviers College, Mumbai as a part of their college project

focault-pendulum-rk4

We analysed the equation of motion using langrangian mechanics and solved the equations which are two coupled 2nd order differential equation using Runge-Kutta 4th order( RK4) numerical method. We then studied how to variations in different parameter effect the motion of the pendulum. by Kunal Singh, Vidhi Tailor and Nilay Ghalsasi

hybrid-nuclear-model-machine-learning-semf-

We first make a theoretical model(using Semi empirical mass formula) and a machine learning model, we compare their results and then finally we use the predictions from the theoretical model as a feature for a new ML model we call this the hybrid model. We finally compare the accuracy of these models.

nlp-projects

LIST of several NLP projects I worked on

timeseries_forecasting_example

In this project, we have shown univariate timeseries forecasting using LSTM and GRU models. We have compared different results and analysed which features are best suited for forecasting.