I love building things. This blog in itself is one of these things. Feel free to shoot me an email.

Posts

• QuickStart for Let's Encrypt on Kubernetes

EDIT 2019-10-31: I tried to update this guide to 0.11, as a lot of things have changed since the original publication. I haven’t tested the full guide in the new version yet, but it should work. EDIT 2019-12-09: Updated for 0.12 and helm3 This post will show you how to use cert-manager to automatically create and use certificates with Let’s Encrypt on Kubernetes. This is especially useful if you are...

• A fork on Github is no fork

Github may block access to your repos and there is nothing you can do about it A few years ago I made a project with a friend and we collaborated on Github in his private repo. After we finished the project I forked it, to be able to still access it independently from him. While I still have unlimited private repos, my friend let his Premium Account (Student) expire. The...

• Machine Intelligence I - Learning Notes

This semester learning notes are about supervised learning. Previous semester on unsupervised learning Performance Measurement Neural Networks Support Vector Machines Bayesian Networks Reinforcement Learning Statistical Learning Theory(Excluded from the exam and therefore neglected here)

• Reinforcement Learning

These are exam preparation notes, subpar in quality and certainly not of divine quality. See the index with all articles in this series In reinforcement learning an actor is in a world where she can perform different actions and perceive the environment. Sometimes there may be rewards. Reinforcement learning is about choosing a policy from which to derive actions that maximize the reward. Just like the real world there are...

• 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...

• 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...
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....
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...