Skip to content

StephRoark/Machine-Learning

BranchesTags
 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

90 Commits
50_Startups.csv
50_Startups.csv
 
 
Ads_CTR_Optimisation.csv
Ads_CTR_Optimisation.csv
 
 
Apriori Findings.pdf
Apriori Findings.pdf
 
 
Apriori.R
Apriori.R
 
 
Apriori.py
Apriori.py
 
 
Artificial Neural Networks Findings.pdf
Artificial Neural Networks Findings.pdf
 
 
Artificial Neural Networks.R
Artificial Neural Networks.R
 
 
Artificial Neural Networks.py
Artificial Neural Networks.py
 
 
Churn_Modelling.csv
Churn_Modelling.csv
 
 
Classification Findings.pdf
Classification Findings.pdf
 
 
Classification Template.R
Classification Template.R
 
 
Classification Template.py
Classification Template.py
 
 
Clustering Template.R
Clustering Template.R
 
 
Clustering Template.py
Clustering Template.py
 
 
Convolutional Neural Networks Findings.pdf
Convolutional Neural Networks Findings.pdf
 
 
Convolutional Neural Networks.py
Convolutional Neural Networks.py
 
 
Decision Tree Classification.R
Decision Tree Classification.R
 
 
Decision Tree Classification.py
Decision Tree Classification.py
 
 
Decision Tree Regression.R
Decision Tree Regression.R
 
 
Decision Tree Regression.py
Decision Tree Regression.py
 
 
Dimensionality Reduction Findings.pdf
Dimensionality Reduction Findings.pdf
 
 
Eclat.R
Eclat.R
 
 
Epoch (ANN)
Epoch (ANN)
 
 
Epoch (CNN)
Epoch (CNN)
 
 
Grid Search.R
Grid Search.R
 
 
Grid Search.py
Grid Search.py
 
 
Hierarchical Clustering Findings.pdf
Hierarchical Clustering Findings.pdf
 
 
Hierarchical Clustering.R
Hierarchical Clustering.R
 
 
Hierarchical Clustering.py
Hierarchical Clustering.py
 
 
K-Fold Cross Validation.R
K-Fold Cross Validation.R
 
 
K-Fold Cross Validation.py
K-Fold Cross Validation.py
 
 
K-Means Clustering Findings.pdf
K-Means Clustering Findings.pdf
 
 
K-Means Findings.pdf
K-Means Findings.pdf
 
 
K-Nearest Neighbors.R
K-Nearest Neighbors.R
 
 
K-Nearest Neighbors.py
K-Nearest Neighbors.py
 
 
KMeans.R
KMeans.R
 
 
KMeans.py
KMeans.py
 
 
Kernel PCA.R
Kernel PCA.R
 
 
Kernel PCA.py
Kernel PCA.py
 
 
Kernel SVM.R
Kernel SVM.R
 
 
Kernel SVM.py
Kernel SVM.py
 
 
Logistic Regression Findings.docx
Logistic Regression Findings.docx
 
 
Logistic Regression Findings.pdf
Logistic Regression Findings.pdf
 
 
Logistic Regression.py
Logistic Regression.py
 
 
ML Template.R
ML Template.R
 
 
ML Template.py
ML Template.py
 
 
Mall_Customers.csv
Mall_Customers.csv
 
 
Market_Basket_Optimisation.csv
Market_Basket_Optimisation.csv
 
 
Multiple Linear Regression Findings.pdf
Multiple Linear Regression Findings.pdf
 
 
Multiple Linear Regression.R
Multiple Linear Regression.R
 
 
Multiple Linear Regression.py
Multiple Linear Regression.py
 
 
Naive Bayes.R
Naive Bayes.R
 
 
Naive Bayes.py
Naive Bayes.py
 
 
Natural Language Processing Findings.pdf
Natural Language Processing Findings.pdf
 
 
Natural Language Processing.R
Natural Language Processing.R
 
 
Natural Language Processing.py
Natural Language Processing.py
 
 
Polynomial Regression Findings.pdf
Polynomial Regression Findings.pdf
 
 
Polynomial Regression.R
Polynomial Regression.R
 
 
Polynomial Regression.py
Polynomial Regression.py
 
 
Position_Salaries.csv
Position_Salaries.csv
 
 
Principal Component Analysis.R
Principal Component Analysis.R
 
 
Principal Component Analysis.py
Principal Component Analysis.py
 
 
README.md
README.md
 
 
Random Forest Classification.R
Random Forest Classification.R
 
 
Random Forest Classification.py
Random Forest Classification.py
 
 
Random Forest Regression.R
Random Forest Regression.R
 
 
Random Forest Regression.py
Random Forest Regression.py
 
 
Regression Template.R
Regression Template.R
 
 
Regression Template.py
Regression Template.py
 
 
Restaurant_Reviews.tsv
Restaurant_Reviews.tsv
 
 
SVM.R
SVM.R
 
 
SVM.py
SVM.py
 
 
SVR.R
SVR.R
 
 
SVR.py
SVR.py
 
 
Salary_Data.csv
Salary_Data.csv
 
 
Simple Linear Regression.R
Simple Linear Regression.R
 
 
Simple Linear Regression.py
Simple Linear Regression.py
 
 
Social_Network_Ads.csv
Social_Network_Ads.csv
 
 
Thompson Sampling.R
Thompson Sampling.R
 
 
Thompson Sampling.py
Thompson Sampling.py
 
 
Upper Confidence Bound.R
Upper Confidence Bound.R
 
 
Upper Confidence Bound.py
Upper Confidence Bound.py
 
 
Wine.csv
Wine.csv
 
 
XGBoost.R
XGBoost.R
 
 
XGBoost.py
XGBoost.py
 
 
apyori.py
apyori.py
 
 
random_selection.R
random_selection.R
 
 
random_selection.py
random_selection.py
 
 

Repository files navigation

ML

A collection of ML classifications. Included in the files is the datasets (csv files) they pull from.

See PDF files for graphed results.

About

No description, website, or topics provided.

Resources

Readme
Activity

Stars

1 star

Watchers

1 watching

Forks

0 forks
Report repository

Releases

No releases published

Packages

No packages published

Languages

  • Python 61.6%
  • R 38.4%