Locating the Algorithm You Need for Machine Learning

TensorFlow For Dummies

There are a number of different algorithms you can use for machine learning. However, finding the specific algorithm you want to know about can be difficult. This table provides you with the online location for information about the algorithms used in machine learning.

Algorithm	Type	Python/R URL
Naive Bayes	Supervised classification, online learning	http://scikit-learn.org/stable/modules/naive_bayes.html https://cran.r-project.org/web/packages/bnlearn/index.html
PCA	Unsupervised	http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.PCA.html https://cran.r-project.org/web/packages/ggfortify/vignettes/plot_pca.html
SVD	Unsupervised	http://scikit-learn.org/stable/modules/generated/sklearn.decomposition.TruncatedSVD.html https://cran.r-project.org/web/packages/svd/index.html
K-means	Unsupervised	http://scikit-learn.org/stable/modules/generated/sklearn.cluster.KMeans.html https://cran.r-project.org/web/packages/broom/vignettes/kmeans.html
K-nearest Neighbors	Supervised regression and classification	http://scikit-learn.org/stable/modules/neighbors.html https://cran.r-project.org/web/packages/kknn/index.html
Linear Regression	Supervised regression, online learning	http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LinearRegression.html https://cran.r-project.org/web/packages/phylolm/index.html
Logistic Regression	Supervised classification, online learning	http://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html https://cran.r-project.org/web/packages/HSAUR/vignettes/Ch_logistic_regression_glm.pdf
Neural Networks	Unsupervised Supervised regression and classification	http://scikit-learn.org/dev/modules/neural_networks_supervised.html https://cran.r-project.org/web/packages/neuralnet/index.html
Support Vector Machines	Supervised regression and classification	http://scikit-learn.org/stable/modules/svm.html https://cran.r-project.org/web/packages/e1071/index.html
Adaboost	Supervised classification	http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.AdaBoostClassifier.html https://cran.r-project.org/web/packages/adabag/index.html
Gradient Boosting	Supervised regression and classification	http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.GradientBoostingClassifier.html https://cran.r-project.org/web/packages/gbm/index.html
Random Forest	Supervised regression and classification	http://scikit-learn.org/stable/modules/generated/sklearn.ensemble.RandomForestClassifier.html https://cran.r-project.org/web/packages/randomForest/index.html

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About the book author:

John Paul Mueller is a freelance author and technical editor. He has writing in his blood, having produced 100 books and more than 600 articles to date. The topics range from networking to home security and from database management to heads-down programming. John has provided technical services to both Data Based Advisor and Coast Compute magazines.

Luca Massaron is a data scientist specialized in organizing and interpreting big data and transforming it into smart data by means of the simplest and most effective data mining and machine learning techniques. Because of his job as a quantitative marketing consultant and marketing researcher, he has been involved in quantitative data since 2000 with different clients and in various industries, and is one of the top 10 Kaggle data scientists.