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
Say “Hello world!” in AI
A Hello World program is usually the first program written by people learning to code. This is how Hello World looks like in C: #include <stdio.h> int main() { // printf() displays the string inside quotation printf("Hello, World!"); return 0; } This is how Hello World looks like in Python: print("Hello, World!") And this is how… Continue reading Say “Hello world!” in AI