Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…medium.com In our previous story (see here) we have looked at the theory behind logistic regression and implemented a very rudimentary version in Rust. For real productive problems this implementation though still is missing many details. …

Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…medium.com This story attempts to explain the theory behind the logistic regression and to give a rudimentary implementation in Rust. Logistic regression is a classic algorithm in supervised machine learning that can be used to estimate conditional probabilities of a categorical outcome variable.

With an example to implement a simple DataFrame. Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…medium.com The type “Any” is not exactly a synonym for something in computer science, but it describes very good what it is good for. Consider the scenario of creating a utility that allows to load table data from a file or some other…

Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…medium.com In our last stories (see here and here) I gave a rough overview about decision trees by looking at its theory and a rudimentary implementation. Although the algorithm’s structure was not difficult, to get all the details done necessary for a production version, is a time consuming task. Luckily, in…

Join Medium with my referral link — applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…medium.com In our previous story (see here), we have seen a prototype implementation of a regression tree. Beside decision trees can be used for regression tasks, they also are a suitable tool for classifications. This can be achieved by a slight change in the algorithm.

A feasible data science task — In machine learning, a decision tree is one of the most basic techniques. It can be used for regressions as well as classifications in supervised learning. Moreover, it can deal with all sorts of feature variables, such as continuous, discrete, categorical, etc. Although decision trees are technically very simple, their…

Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…medium.com This story follows-up and concludes the series about basic aspects in group theory. One of the cornerstone results so far was the decomposition of an commutative, finitely generated group (see here). This led to a split into elements of finite order and elements of infinite order where we have seen…

Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…medium.com In this story we follow-up what we have started here about looking into the so-called Sylow decomposition of a commutative, finite generated group with all elements having finite order. …

Join Medium with my referral link - applied.math.coding Get access to all of my stories and to thousands more on Medium from other writers. As my strong believe is, Medium is…medium.com Now where we have seen the ability to decompose a commutative, finitely generated group into as small as possible non-trivial factors (see here), the natural question arises: Is this decomposition unique? This story aims to provide the necessary tools in order to show such a uniqueness result.