maxgfr/similarities

This package contains functions to find similarities between arrays

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thieu1995/mafese

Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python

Language: Python - Size: 4.51 MB - Last synced at: 24 days ago - Pushed at: 11 months ago - Stars: 72 - Forks: 24

alfonsojimenez/pearson

Pearson correlation coefficient calculator

Language: Ruby - Size: 166 KB - Last synced at: 4 days ago - Pushed at: almost 10 years ago - Stars: 39 - Forks: 4

jendives2000/regressions

Performing of a Linear Regression analysis to determine the strength of the relationship between the number of reviews and sales for a retail company.

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Shwetakhandal/Movierecommendersystem

MovieLens is a well-known database that collects movie ratings, reviews, and metadata. With the rise of streaming services and the exponential growth of content, having an effective recommendation system has become crucial for enhancing user experience. So here is our Movie Recommender System.

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Compcode1/nfl-analysis

The objective of this analysis was to explore potential correlations between player attributes (such as average age and weight across different positions) and key team performance metrics from the 2023 NFL season.

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zick97/mathematical_RecommendationSystems

Non-personalised Bayesian Ranking for dynamic CTR-based rankings and Personalised Pearson Rating Prediction using Collaborative Filtering with Pearson coefficients on the MovieLens dataset.

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Senich17/educational-impact-analysis

A series of analyses to investigate the impact of parental education level on students' math scores.

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allenvox/pearson-correlation 📦

Calculating the Pearson Correlation Coefficient for big data

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Seghelicious/Stuber-Logistics

Predicting the Time Elapsed from Pickup to Delivery

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hshadman/2d_conformational_landscape_map

Use PyConforMap to generate a simple scatter plot to map conformational landscapes of intrinsically disordered proteins, and quantify conformational diversity.

Language: Jupyter Notebook - Size: 23.4 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 0 - Forks: 0

Lefteris-Souflas/Multiple-Regression-Project

Analysis of real estate sales data. Tasks include understanding dataset structure, variable conversion, descriptive analysis, pairwise comparisons, linear relationship analysis, multiple regression modeling, feature selection using stepwise methods, final model summary, assumptions checking, and LASSO variable selection. Results are documented.

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Vaneeza-7/Bayesian-Statistics-Regression-Models-in-pymc3 📦

Bayesian Statistics: Linear Regression and multi-linear models and related concepts (multicollinearity, correlation coefficient etc) on iris dataset in pymc3

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jamestiotio/pns

SUTD ISTD 2021 50.034 Introduction to Probability & Statistics 1D Project

Language: Python - Size: 6.79 MB - Last synced at: about 1 year ago - Pushed at: almost 3 years ago - Stars: 1 - Forks: 0

Ansuman21/Bike-Sharing-Linear-Regression-Case-Study

In this project is a programming assignment wherein you have to build a multiple linear regression model for the prediction of demand for shared bikes. You will need to submit a Jupyter notebook for the same.

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alifallahi/Pearson_correlation_coefficient_PCC

One of the most common techniques for finding similarity between users in RecSys.

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FrankLSilva/all-countries-dataviz

Data vizualitation and several graphs, based on the dataset: AllCountries.csv

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sharmasapna/10-Days-of-Statistics-HackerRank-solutions

10 Days of Statistics Hackerrank Solutions

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Eleen-228/Mall_Customer_Segmentation_Analysis

MySQL + Tableau Project

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Hafez2004/Pearson-Calculator

The Pearson correlation coefficient program is a C++ program that takes input from the user in the form of two vectors of float values, representing two variables X and Y.

Language: C++ - Size: 35.5 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 0 - Forks: 0

bfraser4/Python-Pharmaceutical-Data-Analysis

Pharmaceutical analysis utilizing Python, Pandas, & Matplotlib. Generate summary statistics, create bar charts, scatter plots, and calculate correlation and regression.

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gnsaddy/bookRecommendationSystem

Language: Jupyter Notebook - Size: 18 MB - Last synced at: about 2 years ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 2

bharathvariar/PCA-Implementation

Assignment 2 for CS F320: Foundations for Data Science

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lancepokaiwang/Slow_Down_The_23_Seconds_Death_Clock 📦

Course project for Data 5000

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Sid-149/10-Days-of-Statistics

This repository contains the solutions to HackerRank's 10 Days of Statistics.

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hajarmerbouh/Pyspark_classification

Classification using Pyspark

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RodolpheKouyoumdjian/StocksCorrelation

A program that will return the Pearson correlation coefficient of the stocks entered. One coefficient is returned for each possible pair. The program will plot a heat map and will return a CSV file containing the correlation of each possible stock pair.

Language: Jupyter Notebook - Size: 8.33 MB - Last synced at: about 2 years ago - Pushed at: about 3 years ago - Stars: 2 - Forks: 0

dev-ev/isobaric-correlations

Exploring correlations in an isobaric labeling mass spectrometry-based proteomic data set

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PARSA-MHMDI/correlation

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

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mtzor/MA_project

Social Choice Mechanisms for Recommender Systems. A report of the work is included that describes the project

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yelloejp/projects

Projects of Machine learning and Deep learning

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sagarikamehta/Exploratory-Data-Analysis-on-The-World-Happiness-Report-Datasets

Performed exploratory data analysis (EDA) in python on the world happiness report datasets (for years 2015, 2016, 2017, 2018, and 2019) from Kaggle; to analyze how measurements of well-being can effectively help assess the progress of nations across the world.

Language: Python - Size: 41 KB - Last synced at: almost 2 years ago - Pushed at: over 3 years ago - Stars: 0 - Forks: 0

jai-agrawal/nba-relevant-stats

Investigating the correlation of box stats in the NBA using Pearson Correlation Coefficients.

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