Python for Random Matrix Theory: cleaning schemes for noisy correlation matrices.

Beautiful correlation plots for the terminal

Python library for Random Matrix Theory, cleaning schemes for correlation matrices, and portfolio optimization

Parallel correlation calculation of big numpy arrays or pandas dataframes with NaNs and infs.

This repository should help people that would like to code in R and work with the National Health and Nutrition Examination Survey (NHANES). Some topics corved are SQL , logistic regression.... etc

correlationMatrix is a Python powered library for the statistical analysis and visualization of correlations

Adding Noise Noise Canceling Image resizing Resolution Study Filtering processes -Midic filter -Mean filter -Laplasian filter Photo Sharpening

A Matlab utility for plotting correlation matrices, with similar appearance to Seaborn in Python.

Examples demonstrating the nAG Library for Java

JED is a program for performing Essential Dynamics of protein trajectories written in Java. JED is a powerful tool for examining the dynamics of proteins from trajectories derived from MD or Geometric simulations. Currently, there are two types of PCA: distance-pair and Cartesian, and three models: COV, CORR, and PCORR.

This repository contains Exploratory Data Analysis in Python on Autism Behavioural Challenges on children(0-18 years) dataset

My fictitious firm, GDSMC Global, is a security consultancy focusing on supporting governments around the world in understanding, predicting, and stopping terrorism attacks. Our goal is to allow individual nation states to better deploy security resources to reduce the likelihood of successful terrorism in the future, and to understand what are …

Making use of R programming, the analysis is focussed on the problem which insurance providers are facing today to define their target market and plan their sale strategies which helps them increase their market share and thereby, maximize their profitability. The analysis techniques used in the project are learnt through Data Analysis and Decis…

📊 Visualization of flow structure in cylinder

CryptoIntel is a one stop dashboard which gives all the information about cryptocurrencies. All the inquisitive users can get their answers related to cryptocurrencies from cryptointel.

In this Notebook, I analyze the following five semiconductor stocks: HD, INTC, AMD, MU, NVDA, and TSM. Then, I choose the stock with the least correlation to JNJ in order to diversify a portfolio. The data was generated using the GOOGLEFINANCE historical market data script.

This repository focuses on the projects that I would be doing on "Linear Regression". Feel free to make any improvements. Thanks

Forecasting time series data using ARIMA models. Used covariance matrix to find dependencies between stocks.

Portfolio credit risk modeling

Interactive data visualizations for Kaggle Brooklyn Home Sales data, built using D3.js