Although extremely useful for visualizing high-dimensional data, t-SNE plots can sometimes be mysterious or misleading. By exploring how it behaves in simple cases, we can learn to use it more effectively. A po
Scikit learn is used to visualize high dimensional data, and tsne is the reduction of nonlinear dimensionality technique used to visualize the data into dimensional space. The API of scikit learn will provide a class of tsne to visualize the data using the tsne method. In the below example, w...
From time to time, the visual recipes to perform certain tasks in Dataiku are not enough for what you want to do. In that case you can make use ofcode recipes. Different languages are supported, Python, Scala, SQL, shell and R. To edit the R code you are provided with an editor in...
tuning block-wise effect on the CNN's performance, and that is where this study will come into use: where the effect of each block in three CNN architectures will be investigated to detect how deeply the CNN should be fine-tuned given that fine-tuning a CNN is very computationally ...
In this section, we are going to look at how we can use the t-SNE practically for dimensionality reduction through implementation in python. Before implementation, we are required to know thatsklearnis a library that provides the function for implementing t-SNE under the manifold package. Let’...