Virtues in arguments:

1. Validity
2. Soundness

Relation between premises and conclusion

In a deductive argument, the conclusion should follow from the premises

A deductive argument is supposed to be valid. An Inductive argument is not supposed to be valid.

The Problem of the Skeptical Regress means to trace the reason of an argument recursively. It could be endless. Therefore, it is a problem.

To solve Skeptical Regress problem, we have three ways,

1. Assuring
2. Guarding
3. Discounting

The idea of a principle component is that it is a direction in the data with the largest variation. The algorithm first centres the data by substracting off the mean, and then chooses the direction with the largest variation and places an axis in that direction, and then looks at the variation that remains and finds another axis that is orthogonal to the first and covers as much of the remaining variation as possible. It then iterates this until it has run out of possible axes. The end result is that all the variation is along the axes of the coordinate set, and so the covariance matrix is diagonal - each new variable is uncorrelated with every variable except itself. Some of the axes that are found last have very little variation, and so they can be removed without affecting the variability in the data.

AWS Lambda is a compute service where you can upload your code to AWS Lambda and the service can run the code on your behalf using AWS infrastructure.

The key idea of restricted Boltzmann machine:

A restricted Boltzmann machine which consists of a layer of stochastic binary “visible” units that represent binary input data connected to a layer of chochastic binary hidden units that learn to model significant nonindependencies between the visible units.

There are undirected connections between visible and hidden units but no visible-visible or hidden-hidden connections.

An RBM is type of Markov random field (MRF) but differs from most of MRFs in several ways: it has a bipartite connectivity graph, it does not usually share weights between different units, and a subset of the variables are unobserved, even during training.