Machine Learning

Double Machine Learning for Dummies as explained by ChatGPT

I asked ChatGPT to: explain double machine learning for dummies Here is the answer: Double machine learning (DML) is a statistical method used to estimate treatment effects in the presence of high-dimensional controls. To put it simply, it’s a way to answer questions about cause and effect using data and machine learning, even when there […]

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Cosine similarity in Python

Cosine similarity is the normalised dot product between two vectors. I guess it is called “cosine” similarity because the dot product is the product of Euclidean magnitudes of the two vectors and the cosine of the angle between them. If you want, read more about cosine similarity and dot products on Wikipedia. Here is how

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How to do backpropagation in Numpy

I have adapted an example neural net written in Python to illustrate how the back-propagation algorithm works on a small toy example. My modifications include printing, a learning rate and using the leaky ReLU activation function instead of sigmoid. import numpy as np # seed random numbers to make calculation # deterministic (just a good

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(Tentative)

Symbiosen mellem mennesker og AI vil kunne transformere mennesket til en rationel organisme (jvf. Daniel Kahneman som har påvist at mennesket for sig selv ikke er en rationel organisme). Hvordan det? Vores minutiøse adfærd bliver i stigende grad sporet i alle livets væsentlige forhold. Kunstig intelligens bliver bedre og bedre til at skønne om vi

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PyBrain quickstart and beyond

After pip install bybrain, the PyBrain the quick start essentially goes as follows: from pybrain.tools.shortcuts import buildNetwork from pybrain.structure import TanhLayer from pybrain.datasets import SupervisedDataSet from pybrain.supervised.trainers import BackpropTrainer # Create a neural network with two inputs, three hidden, and one output net = buildNetwork(2, 3, 1, bias=True, hiddenclass=TanhLayer) # Create a dataset that matches

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