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t-distributed-stochastic

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RezaSaadatyar / Machine-Learning-in-Python

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This repository contains functions/codes related to different methods of machine learning for classification and clustering in python.

random-forest clustering naive-bayes machine-learning-algorithms classification logistic-regression support-vector-machine adaboost decision-trees gaussian-mixture-model principal-component-analysis k-nearest-neighbours singular-value-decomposition k-means-clustering multilayer-perceptron independent-component-analysis t-distributed-stochastic feature-selection-methods feature-extraction-methods linear-discrimination-analysis
  • Updated Jul 29, 2024
  • Jupyter Notebook

Develop-Packt / t-Distributed-Stochastic-Neighbor-Embedding

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You will learn to implement t-SNE models in scikit-learn and explain the limitations of t-SNE. Being able to abstract high-dimensional information into lower dimensions will prove helpful for visualization and exploratory analysis, as well as in conjunction with the clustering algorithms. By the end of this course, you will be able to find clus…

unsupervised-learning perplexity stochastic-neighbor-embedding t-distributed-stochastic neighbor-embedding
  • Updated Mar 20, 2020
  • Jupyter Notebook

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