This repositorie includes some notebooks that implement several manifold learning techniques for dimentionality reduction.
The techniques used are ISOMAP, LLE and t-SNE that are tested in three different data sets.
Particularly, the t-SNE exploration also includes some Neural networks tool to embeed new elements in a map, by learning the distribution.
The dataset from the fruits test is a folder containing 130 images of 13 different fruits in different stages of maturity that could be found in the next linkhttps://drive.google.com/drive/folders/1Zx1qiZn0ceI2_BlaqDRHR9AzsBoCYdej?usp=sharing