lemonfold.io 2023-08-08T06:55:51.149723+00:00 ABlog lemonfold.io/posts/2022/dbc/typed_decorator/ 2022-09-15T00:00:00+02:00 Stefan Ulbrich <div class="ablog-post-excerpt docutils container"> <p>This is my very first blog post! In this short post, I will show the blueprint for a fully-typed Python decorator that optionally accepts parameters.</p> </div>

This is my very first blog post! In this short post, I will show the blueprint for a fully-typed Python decorator that optionally accepts parameters.

2022-09-03T00:00:00+02:00 lemonfold.io/posts/2022/aiml_essentials/part1/aiml-essentials-part1/ 2022-10-29T00:00:00+02:00 Stefan Ulbrich <div class="ablog-post-excerpt docutils container"> <p>This article is the start of a series that introduces different models and algorithms to beginners</p> </div>

This article is the start of a series that introduces different models and algorithms to beginners

2022-10-29T00:00:00+02:00 lemonfold.io/posts/2022/aiml_essentials/part2/aiml-essentials-part2/ 2023-01-15T00:00:00+01:00 Stefan Ulbrich <div class="ablog-post-excerpt docutils container"> <p>This is the second part of the series “AI/ML Essentials”, which intends to be a gentle introduction to the topic using mostly layman’s terms and as little mathematics as possible–you don’t need an engineering degree to see the beauty within this fascinating field.</p> </div>

This is the second part of the series “AI/ML Essentials”, which intends to be a gentle introduction to the topic using mostly layman’s terms and as little mathematics as possible–you don’t need an engineering degree to see the beauty within this fascinating field.

2023-01-15T00:00:00+01:00 lemonfold.io/posts/2023/aiml_essentials/part3/aiml-essentials-part3/ 2023-05-26T00:00:00+02:00 Stefan Ulbrich <div class="ablog-post-excerpt docutils container"> <p>In this article in the AI/ML Essentials series, we will learn about yet another machine learning model—Gaussian Process Regression. In the previous articles, we encountered instances of <em>unsupervised</em> learning (for clustering and density estimation). The last issue presented a simple taxonomy of machine learning, which guides us through the series:</p> </div>

In this article in the AI/ML Essentials series, we will learn about yet another machine learning model—Gaussian Process Regression. In the previous articles, we encountered instances of unsupervised learning (for clustering and density estimation). The last issue presented a simple taxonomy of machine learning, which guides us through the series:

2023-05-26T00:00:00+02:00 lemonfold.io/posts/2023/citrate/introduction/ 2023-07-01T00:00:00+02:00 Stefan Ulbrich <div class="ablog-post-excerpt docutils container"> <p>Data science with rust! Finally, two years after having started to learn and develop in the <a class="reference external" href="https://www.rust-lang.org/">Rust programming language</a>, I am happy to find the time to write about my two projects that I have been developing in my rare spare time during the last year.</p> </div>

Data science with rust! Finally, two years after having started to learn and develop in the Rust programming language, I am happy to find the time to write about my two projects that I have been developing in my rare spare time during the last year.

2023-07-01T00:00:00+02:00 lemonfold.io/posts/2023/citrate/cerebral/cerebral_part1_motivation/ 2023-07-02T00:00:00+02:00 Stefan Ulbrich <div class="ablog-post-excerpt docutils container"> <p>In this blog post, I want to announce <a class="reference external" href="https://github.com/StefanUlbrich/citrate/tree/main/cerebral-rs">Cerebral</a> a framework written in Rust for experimenting with Self-organizing Neural Networks such as the famous <a class="reference external" href="https://en.wikipedia.org/wiki/Self-organizing_map">Kohonen networks</a>. It is designed in a way that a network can be defined by composing a model out of a variety of algorithm that define its behavior. Unlike deep learning architectures, the behavior is not defined by a composition of layers, loss functions and diverse learning methods. This type of network defines a less hierarchical topology and learning rules affect all neurons at once. Therefore, this project has different goals as prominent deep learning frameworks, and thus, a different architecture. Being my first Rust library (applications are simpler to implement), I had to evaluate a few options to achieve my goal and I often failed enough battling with Rust’s occasionally frustrating type system.</p> </div>

In this blog post, I want to announce Cerebral a framework written in Rust for experimenting with Self-organizing Neural Networks such as the famous Kohonen networks. It is designed in a way that a network can be defined by composing a model out of a variety of algorithm that define its behavior. Unlike deep learning architectures, the behavior is not defined by a composition of layers, loss functions and diverse learning methods. This type of network defines a less hierarchical topology and learning rules affect all neurons at once. Therefore, this project has different goals as prominent deep learning frameworks, and thus, a different architecture. Being my first Rust library (applications are simpler to implement), I had to evaluate a few options to achieve my goal and I often failed enough battling with Rust’s occasionally frustrating type system.

2023-07-02T00:00:00+02:00 lemonfold.io/posts/2023/rust/sorting_ndarray/ 2023-08-08T00:00:00+02:00 Stefan Ulbrich <div class="ablog-post-excerpt docutils container"> <p>I came across a problem where I needed to sort an array by its values in one column and potentially sort other arrays with that index. In Python, this is <em>very</em> easy:</p> </div>

I came across a problem where I needed to sort an array by its values in one column and potentially sort other arrays with that index. In Python, this is very easy:

2023-08-07T00:00:00+02:00