ML (Machine Learning Newbie)

Implementations of basic machine learning algorithms and their applications in data analysis, etc.

Topics

Supervised learning algorithms: Regression, Classification, Decision Tree, etc.

Clustering algorithms: k-means++, hierachical clustering, etc.

Dimensionality reduction algorithms: LPP, FDA, LFDA, PCA, etc.

Applications: Text Classifier, Simple Twitter analysis, Recommendation System, Searching and Ranking, etc.

Other: Adaboost, kNN, NMF, etc.

Duong Nguyen @TokyoTech

Email: nguyen@sg.cs.titech.ac.jp; ntduong268(at)gmail.com

Name		Name	Last commit message	Last commit date
Latest commit History 84 Commits
DecisionTree		DecisionTree
Dimensionality-Reduction		Dimensionality-Reduction
Ensemble-Methods		Ensemble-Methods
Feed-Clustering		Feed-Clustering
Fisher-Discriminant-Analysis		Fisher-Discriminant-Analysis
KMeans-Clustering		KMeans-Clustering
Locality-Preserving-Projections		Locality-Preserving-Projections
ML@Hackerrank		ML@Hackerrank
Matrix-Factorization		Matrix-Factorization
Misc		Misc
Projection-Pursuit		Projection-Pursuit
Recommendation		Recommendation
Search-And-Rank		Search-And-Rank
Text-Classifier		Text-Classifier
Twitter-Analysis		Twitter-Analysis
logistic-regression		logistic-regression
.gitattributes		.gitattributes
.gitignore		.gitignore
LICENSE.md		LICENSE.md
README.md		README.md