Sagnik Gupta's repositories
A-Multi-Level-Polygonal-Approximation-Based-Shape-Encoding-Framework-for-Automated-Shape-Retrieval
In this repository, we develop a shape descriptive framework using multi-stage polygonal approximation for computer vision based image retrieval.
Advanced-Problem-Solving
In this repository, we solve a list of famous coding problems in C++ programming language.
Precipitation-and-Temperature-wise-prediction-of-risk-in-Indian-territory
In this project, we predict the probability of occurrence of risk in the Indian territory, based on the historical data of precipitation and temperature between the years 1951 - 2015
BigInteger-Library
Big Integer Library in C++. We performed fast exponentiation, GCD of 2 integers, and factorial of an integer.
Inode-based-File-System
In this repository, we implement a inode based file system on top of a virtual disk, designing our own methods for creating a file system, mounting and unmounting it, and basic file operations.
ML_KNN-Decision-Tree
In this repository, we explored the topics of K-nearest neighbors and Decision trees.
ML_PCA-Logistic-Regression-MLP-CNN-SVM
In this repository, we explored the topics of Logistic Regression, SVM and also some of the Deep learning techniques.
ML_SVM-GMM-Linear-Regression-K-Means-Clustering
In this repository, we explored the topics of Linear Regression, SVM, GMM and K-Means clustering.
Tom-and-Jerry-Emotion-Detection
In this repository, we build a deep learning model that detects emotions of Tom and Jerry characters in a video frame.
Drug-Discovery-for-COVID19
We prepare a machine learning model that can be used to propose potential novel effective drugs to fight SARS-CoV-2, the virus responsible for COVID-19.
Fake-News-Identification
In this repository, we propose different machine learning and deep learning models for identification of fake news in online media.
COVID-19-emergency-prediction
In this repository, we aim at predicting the states that might go into a potential emergency situation due to the COVID-19 pandemic.
CraftML-An-Efficient-Clustering-based-Random-Forest-for-Extreme-Multi-label-Learning.
We explore extreme multi label learning using a random forest based algorithm. The parallelized implementation uses a K-Means clustering based partitioning approach to improve performance.
Hate-Speech-Classification
In this repository, we dive into a famous natural language processing problem, where we classify a piece of text as hate speech or not.
Implementation-of-a-deque-and-data-structure-for-LRU-cache
In this repository, we designed a LRU (Least Recently Used) cache.