Dimensionality reduction Question Title * 1. Why do we need Dimensionality reduction? Dimensionality reduction allows to visualize multidimensional data (4 and more). Dimensionality reduction allows to represent multidimensional data using less information (features). None of the variants. Question Title * 2. We can apply dimensionality reduction algorithm on top of the data taken from other dimensionality reduction algorithm: False. True. Question Title * 3. PCA is a distribution based technique: False. True. Question Title * 4. What is n_components used for in PCA and TSNE? It is used for defining expected numbers of output dimensions. + It is used to set up seed, so that results could be reproducible. It is used for defining scale component in order to normalize the data. Question Title * 5. What is length of data frame used in notebook? 569. 689. 348. 345. Question Title * 6. Is it possible to represent image by lower dimensions and still visually maintain same view results? True. False. Готово