so many interests, so little time
we describe an approach for deciding which interests to pursue given that time is limited
we describe an approach for deciding which interests to pursue given that time is limited
we derive the backpropagation equations used to correct the weights for a 3 layer neural net with an arbitrary number of neurons
We create a three layer neural net that can identify handwritten numbers and use a regularization technique called dropout to prevent overfitting
we can best understand how neural nets work by studying a small, simplified example
unsupervised learning algorithms such as Isomap and K-means can produce intuitive categorizations for unlabeled data
we can use distance-preserving maps to simplify and get a useful overview of our data
by rotating a noisy line we can better understand the meaning of principal component decomposition
we perform principal component analysis on song data from 1950 to 2010 and interpret the transformed variables
we use random forest decision tree aggregation to study the gender wage gap in the US from 2012
a vector support classifier can help identify whether a mushroom is edible (but beware!)