Dimentionality reduction and data visualization
Published:
Individual school project on dimensionality reduction technics.
The goal of this project was to get familiar with dimensionality technics: PCA (Principal Components Analysis), LLE (Locally linear Embedding), TSNE (t-distributed Stochastic Neighbor Embedding), LEM (Laplacian EigenMap) and auto-encoders, and to compare them on several datasets.
The main programming languages and packages used are: Python, Scikit-learn, TensorFlow.
The report (in French) is available here.