Pytorch, Machine Learning, Gradient Descent, Python, Hands On Tutorials.
extent=[-5, 8, -5, 8]) ax.title.set_text(title) loss_w, loss_b = zip(*models) ax.scatter(loss_b, loss_w, c='r', marker='+') ax.plot(loss_b, loss_w, c='r') plt.show() multi_plot(lr=0.1, epochs=100) Figure 5. Visualized gradient descent down all loss functions. Here we can see the interesting