Editorial course preview
What the public course preview actually shows
These 4 complementary views highlight concrete, legible examples from the course presentation.
This slide illustrates the architecture of an autoencoder neural network, detailing the flow from input to encoded and decoded layers alongside key applications.
This slide introduces Restricted Boltzmann Machines as unsupervised learning models similar to autoencoders, illustrated with a diagram showing the connections between visible and hidden layers.
This slide introduces t-SNE as a powerful tool for data visualization and dimension reduction, displaying a clustered scatter plot alongside the instructor.
This slide introduces Principal Components Analysis as a fundamental algorithm used in data science, finance, engineering, and biology, illustrated with PCA scatter plots.