I love building things. This blog in itself is one of these things. Feel free to shoot me an email.
Posts
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Support Vector Machines
These are exam preparation notes, subpar in quality and certainly not of divine quality. See the index with all articles in this series If you are stuck, read Wikipedia in parallel. The goal of SVMs is to divide two groups with a line that separates the data points as clearly as possible. There are two cases: Data points can be cleanly split into their classes At least some data points...
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Performance measures
These are exam preparation notes, subpar in quality and certainly not of divine quality. See the index with all articles in this series Choice of error function Usually squared error is used. Cross-Entropy \(c\) := different classes (classification / symbol representation) From Wikipedia: In information theory, the cross entropy between two probability distributions p and q over the same underlying set of events measures the average number of bits needed...
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Neural Networks
These are exam preparation notes, subpar in quality and certainly not of divine quality. See the index with all articles in this series Connectionist Neurons A neural network generally has a number of inputs \(x_1...x_N\) which are aggregated into \(\underline x\). At each node there is a transfer function \(y_i\) which turns the inputs according to weights \(\underline w\) into its own output. A typical function would look like this....
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Bayesian Networks
These are exam preparation notes, subpar in quality and certainly not of divine quality. See the index with all articles in this series Bayes Rule \[P(A|B) = \frac{P(B|A)P(A)}{P(B)}\] Inference Bayesian Interference is about inferring probabilities from prior probabilities. Given a set of prior events, a bayesian network estimates the probability for another event. Justification of using heuristics: In real-world scenarios you never know the true probability of events. To somehow...
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Statistical Learning Theory
These are exam preparation notes, subpar in quality and certainly not of divine quality. See the index with all articles in this series In a classification problem the desired goal is to reduce the generalization error \(E^G\). Unfortunately during training it is only possible to evaluate the classifier against a limited amount of data - the test data set. Therefore we can only measure \(E^T\). The problem we want to...
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34C3 Economics of Climate Change Lightning Talk
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Docker Images with Gitlab CI
You want to have docker tags that match your git branches? Here is how to do it with Gitlab CI. A lot of my projects have a CI pipeline that builds a docker image. Of course I do not want to always deploy the :latest tag, because that makes reproducibility and rollbacks hard. I always push to :latest. Also I want to reference by: tags/branches commit hash For this repo...
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34C3 Day 1
Day one of the 34C3 is over. The new location in Leipzig is a lot more spacey and loftey, but I liked the old location in the CCH more. Somehow I felt that there were fewer easter-eggs and hidden nuggets than in previous congresses. I guess everyone still needs to adapt to the new environment. Hopefully in the coming days there will be more. Tomorrow will also be my first...
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