The following pages and posts are tagged with
| Title | Type | Excerpt |
|---|---|---|
| Eigen Decomposition | Page | Note: Please utilize the template below as a reference for your contribution. Adapt the template when deemed necessary What is TOPIC-NAME? Brief description. Recommended Path for Learning This page introduces what eigendecomposition is. This reads like a short summary of... |
| K-Means Clustering | Page | Note: Please utilize the template below as a reference for your contribution. Adapt the template when deemed necessary What is TOPIC-NAME? Brief description. Recommended Path for Learning Item 1 (video/code tutorial/document) Item 2 (video/code tutorial/document) Item 3 (video/code tutorial/document) <h2... |
| Locally Linear Embeddings | Page | Locally linear embedding is a method for computing low-dimensional embeddings of data distributed as nonlinear manifolds in the higher-dimension space |
| Logistic and Multinomial Regression | Page | Note: Please utilize the template below as a reference for your contribution. Adapt the template when deemed necessary What is TOPIC-NAME? Brief description. Recommended Path for Learning Item 1 (video/code tutorial/document) Item 2 (video/code tutorial/document) Item 3 (video/code tutorial/document) <h2... |
| Naive Bayes Classifiers | Page | Note: Please utilize the template below as a reference for your contribution. Adapt the template when deemed necessary What is TOPIC-NAME? Brief description. Recommended Path for Learning Item 1 (video/code tutorial/document) Item 2 (video/code tutorial/document) Item 3 (video/code tutorial/document) <h2... |
| Principal Components Analysis | Page | PCA is a method of data reduction that plots data along dimensions that explain the greatest variance in the data |
| Random Forests | Page | Note: Please utilize the template below as a reference for your contribution. Adapt the template when deemed necessary What is TOPIC-NAME? A random forest is an “ensemble” method made up of a collection of decision-tree models. In general, random forest models make reasonable... |
| Spectral Clustering | Page | Note: Please utilize the template below as a reference for your contribution. Adapt the template when deemed necessary What is TOPIC-NAME? Brief description. Recommended Path for Learning Item 1 (video/code tutorial/document) Item 2 (video/code tutorial/document) Item 3 (video/code tutorial/document) <h2... |
| Spectral Clustering | Page | Note: Please utilize the template below as a reference for your contribution. Adapt the template when deemed necessary What is a Spectral Clustering? Spectral clustering is a family of methods by which one can find clusters in a data set, which is under... |
| Support Vector Machines | Page | Support vector machines are models for binary classification. |
| Singular Value Decomposition | Page | Note: Please utilize the template below as a reference for your contribution. Adapt the template when deemed necessary What is TOPIC-NAME? Brief description. Recommended Path for Learning Item 1 (video/code tutorial/document) Item 2 (video/code tutorial/document) Item 3 (video/code tutorial/document) <h2... |
| t-Distributed Stochastic Neighbour Embeddings | Page | {% include note.html content="Please utilize the template below as a reference for your contribution. Adapt the template when deemed necessary" %} ## What is t-SNE? t-Distributed Stochastic Neighbor Embedding (commonly known as t-SNE) is a dimension reduction technique that preserves relative distances between points in high-dimensional data. ## Recommended Path... |
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