R codes for common Machine Learning Algorithms
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Updated
May 26, 2017 - R
R codes for common Machine Learning Algorithms
Code for 'High rises and housing stress: A spatial big-data analysis of rental housing financialization'
Repository for Udemy Course: Identify problems with Artificial Intelligence
Designing and applying unsupervised learning on the Radar signals to perform clustering using K-means and Expectation maximization for Gausian mixture models to study ionosphere structure. Both the algorithms have been implemented without the use of any built-in packages. The Dataset can be found here: https://archive.ics.uci.edu/ml/datasets/ion…
It's a package containing functions that allow you to create your own color palette from an image, using mathematical algorithms
Using Machine Learning to find people with similar personalities & interest for matchmaking
Business Intelligence Course work - R Studio (Neural Networks, Deep Learning, Data Warehousing)
K-means clustering on White wine dataset
LearnR tutorial about PCA and k-Means Clustering https://inayatus.shinyapps.io/AlgLearnRUL/
Customer segmentation is the process of dividing customers into groups based on common characteristics so companies can market to each group effectively and appropriately. This Project uses R language and Kmeans clustering algorithm to segment customers into clusters.
Hierarchical clustering and partitional clustering with exploratory factor analysis on chocolate quality.
Clustering event data (StatsBomb) using k-means algorithm in R.
R Markdown script to perform bioinformatic analysis on RNA-seq raw count matrices, including DE-testing via DESeq2 and gene set enrichment analysis (GSEA).
Complete package for all Data Science models using R. Starting form Preprocessing, Data Manipulation, Feature Engineering, Model Building, and Model Validation.
Análise de Clusters utilizando a base de dados de compras anuais dos clientes de um distribuidor atacadista de Portugal (Wholesale Dataset - UCI repository).
Carolina Data Challenge Project - Forgotten America
R project. Output: a Rshiny web app that analyzes thousands of Airbnb France data (Paris, Lyon, Bordeaux). Skills: web app design (Rshiny), data cleaning and preparation (dplyr, lubridate), data visualization (ggplot2), maps (leaflet) and kmeans clustering.
Applied several ML Algorithms
Data Mining Applied to Oil Well Using K-means and DBSCAN (A Research Paper Implementation along with OPTICS and PCA)
Clustering analysis using R
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