NLP, Python, Scikit Learn.
TruncatedSVD(dimensions, n_iter=40).fit_transform(vec_list) def d2_plot(data): plt.plot(data, '.') d2_plot(pca_reduce(x_train,2)) The graph looks a bit different, less outliers on the y-axis with values smaller than 0. Finally, lets view the data as a 3D graph. import matplotlib.pyplot as plt from