pearson-correlation
There are 3 repositories under pearson-correlation topic.
KwokHing / YandexCatBoost-Python-Demo
Demo on the capability of Yandex CatBoost gradient boosting classifier on a fictitious IBM HR dataset obtained from Kaggle. Data exploration, cleaning, preprocessing and model tuning are performed on the dataset
Language:Jupyter Notebook 30pancr9 / Netflix-Recommender-System
ITCS 6190 : Cloud Computing for Data Analysis project. Movie Recommendation Engine for Netflix Data with custom functions implementation and library usage.
Language:Python 27remingm / covid19-correlations-forecast
Web app with interactive forecasts based on correlations
Language:Python 15sohilsshah91 / Spatio-Temporal-Crime-Analysis-Time-Series-NYC
This project gives an overview of crime time analysis in New York City . We have created Python Jupyter notebooks for spatial analysis of different crime types in the city using Pandas, Numpy, Plotly and Leaflet packages. As a second part to this analysis, we worked on ARIMA model on R for predicting the crime counts across various localities in the city based on correlations of various demographics correlation in each locality.
Language:Jupyter Notebook 15tlatkowski / tf-feature-selection
Implementation of various feature selection methods using TensorFlow library.
Language:Python 9gnsaddy / book-recommendation-system-webapp
Book Recommendation System Web App
Language:SCSS 8rubenvar / calculate-correlation
A package that calculates correlation between two arrays. Simple, with no dependencies
Language:JavaScript 8artisan1218 / Recommendation-System
Hybrid RecSys, CF-based RecSys, Model-based RecSys, Content-based RecSys, Finding similar items using Jaccard similarity
Language:Python 7ravexina / python-recommender-system
A simple recommender system in python implementing: ItemKNN, UserKNN, ItemAverage, UserAverage, UserItemAverage, etc.
Language:Python 7- Language:Python 6
breese / trial.online
Online statistics
Language:C++ 5mohan-aditya05 / credit_card_customer_segmentation
Develop a customer segmentation to define market strategy. The sample dataset summarizes the usage behaviour of about 9000 active credit card holders during the last 6 months.
Language:Jupyter Notebook 5shubhamchouksey / Movie-Recommendation
Recommedation of movies to a user based on user rating data.
Language:Jupyter Notebook 5tanvirnwu / Feature-Selection--Python
"A set of Jupyter Notebooks on feature selection methods in Python for machine learning. It covers techniques like constant feature removal, correlation analysis, information gain, chi-square testing, univariate selection, and feature importance, with datasets included for practical application.
Language:Jupyter Notebook 5adarshpalaskar1 / Movie-Recommender-System
Recommendation system built using multiple ML models that aim to predict users' interests based on their past behavior and preferences.
Language:Python 4drbashar315 / COVID_Infection_Rate_VS_Distance_From_Manhattan
Example of an end to end data analysis project starting from data acquisition to development of insights. Raw python is mostly used.
Language:Jupyter Notebook 4IshtyM / Books-Recommender-System-
Books recommendation system by collaborative filtering and certain visualization are done on data.
Language:Jupyter Notebook 4meantrix / corrp
Compute multiple types of correlations analysis (Pearson correlation, R^2 coefficient of linear regression, Cramer's V measure of association, Distance Correlation,The Maximal Information Coefficient, Uncertainty coefficient and Predictive Power Score) in large dataframes with mixed columns classes(integer, numeric, factor and character) in parallel backend.
Language:R 4swilliamc / SAS_StatisticalBusinessAnalyst
SAS Professional Certificate in Statistical Business Analyst using SAS
abishek-as / Netflix-Movie-Recommendation
This repository is for Netflix movie recommendations using various content and collaborative-based methods like Word2vec, Node2vec, Sentence Transformer, MiniBatchKMeans, Cosine Similarity, Pearson's Correlation, and Singular Value Decomposition (SVD).
Language:Jupyter Notebook 3fblupi / recommender-system-cf-java
Recommender System based on Collaborative Filtering using Java
Language:Java 3Gkontopodis / Data-Analysis-Tools
Wesleyan University
Language:Python 3- book-recommendation-system
GNDEC-Minor-Project-KGJ / book-recommendation-system
A recommendation system for books. Built by following two filtering methods that are Collaborative Filtering and Content Based Filtering. Algorithms used are KNN, Pearson Correlation, and TF-IDF. Every dataset used can be easily found in the data folder of the respository.
Language:Jupyter Notebook 3 mdshihabullah / federated-predicted-euclidean-distance
Calculating pairwise euclidean distance matrix for horizontally partitioned data in federated learning environment
Language:Python 3nikolas-virionis / linear-regression-model
An npm package to make it easier to deal with a handful of values, and try to model them in one of the most used mathematical models, with an R/Numpy-like accuracy algorithm
Language:JavaScript 3PARSA-MHMDI / correlation
In this repository, four famous correlation algorithms have been implemented. Pearson, spearman, Chatterjee, and MIC correlation algorithm implemented
Language:Jupyter Notebook 3robotomize / correlation-rank-php
This is a simple implementation of the package to calculate correlation coefficient
Language:PHP 3This is a simple implementation of the package to calculate correlation coefficient
Language:JavaScript 3- Language:Python 2
BALaka-18 / Hybrid-Recommendation-system
A hybrid movie recommendation system
Language:Jupyter Notebook 2gawaksh007 / Books-Recommender
Basic recommender that uses Item based collaborative filtering and suggests books using neighbourhood data.
Language:PHP 2karttiik / Recommender-System
Movie Recommendation System
Language:Java 2rajan2275 / Data-Science-Projects
Data Science Projects
Language:Python 2Yulv-git / Correlation-and-Agreement-Analysis
Statistical analysis for correlation (Pearson Correlation) and agreement (Bland-Altman Agreement). Assessing correlation and agreement between two methods of measurement.
Language:Python 2luceldasilva / covid_19_italia
Una entidad gubernamental responsable de la gestión de la salud en Italia enfrenta el desafío de comprender y analizar la propagación del COVID-19 para tomar decisiones informadas y eficaces en la gestión de la pandemia. Como científico de datos nuestra tarea es presentar insights que responden a las inquietudes de la entidad
Language:Jupyter Notebook 1
