machinelearning-r

There are 1 repository under machinelearning-r topic.

• spsanderson / steveondata

  Repository for mainly R tips and tricks for my blog. I also include some VBA, SQL, C and Linux Usage.

  sqlaidatadata-sciencemachinelearning-rmlrtime-seriestipofthedayblogclinuxms-sqlvbavba-excel
  Language:JavaScript 8

• jordanmendler / project-cheatsheet

  Compilation of cheatsheets related to AI, Machine Learning, Software Development, etc

  aiartificial-intelligencecheatsheetcheatsheetsdeep-learningdeep-learning-tutoriallinuxlinux-shellmachine-learningmachine-learning-algorithmsmachinelearningmachinelearning-pythonmachinelearning-rneural-networkneural-networkspandas-tutorialpythonrtutorialtutorials
  6

• manvimadandotai / workout-training-using-ml

  This repository contains the implementation of the research paper tVelloso, E., Bulling, A., Gellersen, H., Ugulino, W. and Fuks, H., 2013, March. Qualitative activity recognition of weight lifting exercises. In Proceedings of the 4th Augmented Human International Conference (pp. 116-123).

  datascience-machinelearningrprojectmachinelearning-rresearch-projectmachinelearningmachine-learning-algorithms
  Language:R 5

• 7Aishwarya / Machine-Learning

  Machine Learning A-Z™ Hands-On Python & R In Data Science

  machine-learningmachine-learning-in-python-and-rmachine-learning-modelsmachine-learning-in-pythonmachine-learning-in-rmachinelearning-pythonmachinelearning-rmachinelearningmachine-learning-a-to-zmachine-learning-practicelearn-machine-learningmachine-learning-for-beginners
  Language:Python 4

• NiranjanStack / Customer-Behavior-Analysis-in-R-Shiny

  Analyzing transactions of a retailer to predict promotional items.

  predictive-analyticsdata-sciencemachinelearning-rsvm-modelshiny-appsanalysisanalyzing-transactionsretailershiny
  Language:R 4

• trungngv / datascience

  Template for data science projects (R-based) which includes a few useful utilities.

  data-sciencedatasciencermachinelearning-r
  Language:R 4

• AkashSaxenaOfficial / Employee_Absenteeism

  The task is to build a machine learning regression model will predict the number of absent hours. As Employee absenteeism is a major problem faced by every employer which eventually lead to the backlogs, piling of the work, delay in deploying the project and can have a major effect on company finances. The aim of this project is to find an issue which eventually leads toward the absence of an employee and provide a proper solution to reduce the absenteeism

  data-sciencemachine-learning-algorithmsmachinelearning-rmachine-learning-modelsmachine-learning-regressionexploratory-data-analysismissing-valuesfeature-selectionfeature-scalingknn-regressionknn-modeldecision-tree-regressionrandom-forest-regressionlinear-regressordata-analysisdata-visualization
  Language:Jupyter Notebook 3

• fabianofilho / MLS

  Machine Learning in Healthcare Course with R

  insightsreferencescontentfulhealthcaremachinelearning-rdigital-signal-processingawesomehealthcare
  Language:R 3

• beatrizeg / MovieRecommendation

  The goal of this project is to use different Machine Learning algorithms to try to predict the rating that an user will give to a movie. To achieve this, we will use the Machine Learning models and statistics that we have learnt during the Data Science course and we will finally choose the one that gets the minimum RMSE number. The dataset is allocated in http://files.grouplens.org/datasets/movielens/ml-10m.zip and has been pre-processed to achieve the movielens dataset

  machinelearningmachinelearning-rrecommendation-system
  Language:R 1

• devdatta95 / Polynomial-Regression-For-Salary-Prediction

  A simple R program that implements a very basic Polynomial Regression on a small data set. Because these data set don't have liner relationship between independent variable and dependent variable. so if we use the liner model then well get very High error. so in these example w'll compare both the model and select which one is best.

  polynomial-regressionmachinelearning-rdata-sciencerregression-modelsregreession
  Language:R 1

• DohaNaga / Off-target-P-ML

  This repository contains the necessary scripts to derive off-target models through (1) A neural network framework based on Keras and Tensorflow (2)An autmomated machine learning framework based on AutoGluon

  machinelearning-rautomated-machine-learningneural-networkskeras-tensorflowclassification-algorithims
  Language:R 1

• mcmvp9 / propensityscore_analysis

  This repository is associated with propensity score analysis utilizing machine learning algorithms to examine the impact of health insurance on duration of hospital stay in the NYC SPARCS 2015 In-patient discharges dataset.

  machinelearningmachinelearning-rmachinelearningalgorithmspropensity-score-matching
  1

• NisrineBennor / Langage_R_Data_Visualisation_Machine_Learning

  plotlyggplot2ggplot2-themeggplot2-scalescaretsvm-linearsvmdplyrrstudiomachine-learningmachinelearning-rnaive-bayes-classification
  1

• rusergroupstgallen / rusergroupstgallen.github.io

  This is the repo hosting resources of the R User Group at the University of St. Gallen.

  coding-challengedata-visualizationmachinelearning-rrstatisticstutoring-materials
  Language:HTML 1

• sharikalog7 / Corrosion-Rate-Prediction-Using-Machine-Learning

  rprogrammingmachine-learningmachine-learning-algorithmsmachinelearning-rneural-networkrandom-forestxgboostggplot2tidyverse-ggplot2
  Language:HTML 1

• thedvlprguy / CleanEnergyPrediction

  Read The Blog From Here:

  machinemachine-learning-algorithmsmachinelearningmachinelearning-rsupportvectormachinescleanenergy
  Language:Jupyter Notebook 1

• alexandracathcart / portfolio

  datasciencemachinelearning-pythonmachinelearning-rsparkpysparksqlpredictive-analytics
  Language:Jupyter Notebook 0

• ethan-gruis / wine_reviewer

  Using Machine Learning to predict wine review scores based on binarized tasting notes

  machinelearning-rkaggle-dataset
  Language:R 0

• FraMaBu / Alternative-Fuels-Random-Forest

  In this project I am interested in classifying if existing vessels have the option of using alternative fuels based on vessel specific features.

  machinelearning-rtidymodels
  Language:R 0
• helioribeiro.github.io

  helioribeiro / helioribeiro.github.io

  REPOSITORY FOR MY SOFTWARE DEVELOPMENT AND DATA SCIENCE PORTFOLIO.

  csshtmlportfoliobigquerymachinelearning-pythonmachinelearning-rpowerbipythonrjupyterapacheapache-kafkaapache-sparkapiairflowdocker
  Language:CSS 0

• Jeevitha0306 / Bike_Prediction

  This project is to predict number of bikes rented in each bike stations with a temporal granularity of one hour.

  rmachinelearning-rapplied-data-sciencebike-rentalhypothesis-testing
  0

• joewellman / WineRatings

  machine-learningrmachinelearning-rwine-quality-predictionwine-reviews-datasetmachine-learning-algorithmsmachinelearning
  Language:R 0

• justinhamilton125 / Justin_Hamilton_Portfolio

  This is my portfolio containing files I have used for my various projects

  classification-modelsjupyter-notebookmachinelearning-rpythonrstudio
  Language:HTML 0

• occupyed / learn-machine-learning-R

  Master the skills of machine learning with R. Full course code snippets

  rdata-sciencemachine-learningmachine-learning-algorithmsmachinelearning-r
  Language:R 0

• rafahostert / CoffeeShops

  Prever se uma nova Coffee Shop recém aberta consegue obter mais de 450 reviews dentro de um ano com base em suas características

  confusion-matrixdecision-tree-classifierexploratory-data-analysisexploratory-data-visualizationslogistic-regressionmachinelearning-rr
  Language:Jupyter Notebook 0

• rafiqru / machinelearning-towards-a-new-challenge

  machinelearning-r
  0

• rathina98 / car_insurance_claim_pred

  Along with the visualization of the data, classification model was built to predict whether a car gets the insurance claim or not.

  rcaretdplyrggplot2classification-modelsmachinelearning-rprediction
  0

• robertpreseau / RIT_Spotify_Capstone

  This was the Capstone project for my Masters degree. This project looked at data provided by Spotify in an effort to help determine which of 10 future tracks a listener would skip based on their listening history with 10 historical tracks in a session.

  machinelearning-rmachine-learning-algorithmscapstone-project
  Language:R 0

• Rukkha1024 / Improving-Readers-App-Recommendations-with-ML-Analysis

  This project was conducted as part of the 'Data Prediction Model' class during the 2023-1

  machinelearning-r
  Language:R 0

• SayanAndrews2002 / Machine-Learning-Heart-Patient-Data-Project

  Used R to visualize and analyze a dataset of heart patients with many predictor variables. Evaluated several machine learning models, such as logistic, linear discriminant analysis, quadratic analysis model, and K-nearest neighbors model, to find best fit for the data. Used random forests for tuning and cross validation.

  healthcare-datamachinelearning-rheart-diseaser-programmingr-programming-language
  0

• UNC-2021-STOR-565-Proj-1-Group-7 / MINST-Classification

  Classification of handwritten digits using MINST dataset

  machinelearningmachinelearning-rminst
  0

• jlbrosnahan / Predict-Brand-Preference

  Machine learning binary classification RStudio

  machinelearningconfusion-matrixmachinelearning-rbusiness-solutionsrandom-forest-classifier
  Language:R

• KAR-NG / Credit-Card-Market-Segmentation

  VEV model from Mclust among 5 clustering algorithms has optimal performance and detected 8 distinct groups of users. Data was cleaned, standardized and feature-selected, PCA’s biplot, Ggplot, Radar plots, and parallel coordinate plots were applied for EDA.

  claraclusteringdbscanfuzzymachinelearning-rmodel-based-clusteringpcarhkmeans
  Language:R

• KAR-NG / Food-Poison-Survey-Analysis-using-Multiple-Correspondence-Analysis

  This project applies multiple correspondence analysis (MCA) with the techniques in scree plot, variable plots, individual plots, biplot, cosine square (CO2) and contribution statistcs (contrib) to detect trends in the multivariate food poisoning survey dataset and identified the most probable food that caused the food poison. MCA is one of the principal component methods, and principal componet methods belong to the "unsupervised" machine learning branch.

  aimachinelearning-rprincipalcomponentanalysis

• phaecki / Zeitreihenprognose-tidymodels

  Anwendung einer Zeitreihenprognose mit R tidymodels für das Supply Chain Management. | Using R tidymodels to create a time series forecast for supply chain management.

  machine-learningmachine-learning-algorithmsmachinelearningmachinelearning-rrtidymodelingtidymodelstime-series-forecastingtimeseries

• suneelpatel / Machine-Learning-with-R

  This repository serves as an excellent introduction to implementing machine learning algorithms with R in depth such as linear and logistic regression, decision tree, random forest, SVM, Naive Bayes, KNN, K-Mean Cluster, PCA, Time Series Analysis and so on.

  machine-learningmachine-learning-algorithmsmachinelearningmachine-learning-librarysupervised-learningunsupervised-learningrecommender-systemrecommendation-enginetime-series-analysismachinelearning-rdata-science