How can we systemically identify analogous food items across cultures? Learn how using word embeddings.
Visualize large datasets and identify potential clusters with this special breed of neural networks that uses neurons to learn the intrinsic shape of your data.
Do you know what gives red and white wine their colors? Use k-NN to discover the chemical make-up that defines typical types of wines, as well as to detect atypical ones.
Using weapons trade data, we map out who's against who in the complex arena of international politics.
You own a store. How do you discover purchasing patterns, such as which items tend to be bought together? Knowing this can improve your product placement and advertisement.
While an artificial neural network could learn to recognize a cat on the left, it would not recognize the same cat if it appeared on the right. To solve this problem, we introduce convolutional neural networks.
You want to publish ads for your product. While you have 2 promising ad designs, you have a limited budget. How can you find out which ad is more effective, while maximizing the impact of all the ads you publish?
Outliers can be detected by algorithms used for predictions. To illustrate, we use the k-nearest neighbor (kNN) clustering algorithm.