Probabilistic Programming for couples

I will start with a disclaimer, for probabilistic programming to work, both partners should belong to the Bayesian Order and should know their business, i.e. be domain experts (the latter is self-implied). The Bayesian Order differs from the more Traditional Statistical Order by preserving uncertainty. They interpret a probability as measure of belief, or confidence,… Continue reading Probabilistic Programming for couples

Neural Networks as universal problem solvers

The approximate answer to life, the universe and everything is neural networks. At least this is what the Universal Approximation Theorem (UAT) tells us. Or to put it, in more earthly terms, quoting Ian Goodfellow: "A feedforward network with a single layer is sufficient to represent any function, but the layer may be infeasibly large… Continue reading Neural Networks as universal problem solvers