Represent convolution/correlation matrices in Python 2.7 without the need to actually compute them.

Network Analysis for Financial Markets

A bayesian approach to examining default mode network functional connectivity and cognitive performance in major depressive disorder

Find and Compute optimal submatrix of invalid correlation matrix

Comparing the progress of the Corona Virus with trends in Google and Twitter.

Analyze data from bike sharing services to identify usage patterns. Implement visual analysis, hypothesis testing, and time series analysis

Repo where different methods for price regression are used (supervised machine learning)

Exploratory Data Analysis and Visualization-GDP is one of the most important indicator in determining the performance of country economy.The significant factors affecting gdp are population,agriculture,service,industry,health,migration,urban and obesity which are recorded in the dataset. Null hypothesis is that population,agriculture,service,ind…

Implementation of: Clustering of the structures by using "snakes & dragons" approach, or correlation matrix as a signal - https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223267

Different modeling techniques like multiple linear regression, decision tree, and random forest, etc. will be used for predicting the concrete compressive strength. A comparative analysis will be performed to identify the best model for our prediction in terms of accuracy. The best model will be helpful for civil engineers in choosing the approp…

Feature Selection

Heatmap that correlates world cuisines Wikipedia pages with the correspondent Wikipedia languages

Multi-Linear-Reg

📊 A financial correlations library for Elixir, fully compatible with the elixir Decimal library.

Implementation of SVM Classifier To Perform Classification on the dataset of Breast Cancer Wisconin; to predict if the tumor is cancer or not.

Statistical Multivariate Regression Analysis to determine the effects of mortality, economic and social factors on life expectancy.

Construção de um modelo de machine learning para prever com precisão a demanda de estoque com base nos dados históricos de venda do grupo Bimbo.

Apply traditional statistical methods such as PCA and FA to characterize political opinions within survey research data

Clustering project for assessment of Unsupervised Learning lecture (Jacek Lewkowicz)

This package focuses on the tasks of dealing with outlier and missing values, scaling, and correlation visualization.