🔗 Methods for Correlation Analysis

A complete pytorch implementation of skip-gram

Dict2vec is a framework to learn word embeddings using lexical dictionaries.

collection of utility functions for correlation analysis

In this repository, four famous correlation algorithms have been implemented. Pearson, spearman, Chatterjee, and MIC correlation algorithm implemented

Retrieving, Processing, and Visualizing Data with Python

Measuring the Accuracy of Password Strength Meters

Original dissertation title: "Extract Emotional Tags from Movie Synopses". The identification, definition, and automatic prediction of a set of emotions in movies, based on their movie abstracts and various metadata.

SkipGram NegativeSampling implemented in PyTorch.

This repository contains simple statistical R codes used to describe a dataset. These scripts provide a summarized and easy way of estimating the mean, median, mode, skewness and kurtosis of data. It also provides codes for calculating the covariance.

This repository contains the codes of mathematical and statistical methods like Interpolation, Guass Jacobi, Guass Jordan, etc. that I coded in C as a part of course MA403 Probability, Statistics, and Numerical Analysis.

sac project tool

Implementation of Spearman and Kendall correlation coefficient for MS Excel (VBA)

Analysis of two variables by nonparametric method

Spearman's 1904 work on 'General Intelligence' launched the field of factor analysis into existence. This slide-deck discusses the details and aftermath.

A toolkit for estimating the correlation between variables

This project explores the relationship between features and diagnosis in cancer data. Using methods like boxplots, scatterplots, PCA, k-means clustering, and logistic regression, we analyze and visualize data to understand health indicators.

Predicting long-term and short-term Video Memorability using Semantic and Video features.