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Open-source relational database management system (RDBMS)

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Speed Dating with the CodeIgniter 4 on GitHub

Reading time 2 min
Views 2.7K

Getting acquainted with the CodeIgniter 4 PHP framework is quite simple.

Spend the evening following the instructions in the «Build Your First Application» section. Since the documentation is written in a good, technically understandable language, it is even possible to get some aesthetic pleasure in the process of familiarizing yourself with this and other sections.

The feeling of airiness and consistency of the CodeIgniter 4 project will be present with you everywhere now.

What is so attractive about CodeIgniter 4?

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Total votes 7: ↑6 and ↓1 +5
Comments 2

Mysql 8.x Group Replication (Master-Slave) with Docker Compose

Reading time 5 min
Views 5K

This post is handling the following situation - how to setup up simple Mysql services with group replication being dockerized. In our case, we’ll take the latest Mysql (version 8.x.x)

FYI: all mentioned code (worked and tested manually) located here.

I will skip not interested steps like ‘what is Mysql, Docker and why we choose them, etc’. We want to set up possibly trouble proof DB. That’s our plan.

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Machine Learning CPython library 'VKF'

Reading time 14 min
Views 1.3K
Previous article describes a web server for Machine Learning system 'VKF' based on Lattice Theory. This paper is an attempt to explain details of using the CPython library directly. We reproduce working sessions of experiments on datasets 'Mushroom' and 'Wine Quality' from UCI Machine Learning repository. The structures of input files are discussed too.

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Web server for Machine Learning 'VKF-solver'

Reading time 20 min
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Nowadays most people identify Machine Learning with training of various kinds of neural networks. At the beginning there were fully connected networks, then convolutional and recurrent networks replace them, now there exist a quite exotic variants of networks such that GAN and LTSM networks.

Their training requires constantly increasing volume of samples, and they also do not be able to explain why a particular decision was made. Structural approaches to Machine Learning avoiding these drawbacks exist, the software implementation of one of which is described in the article. This is an English translation of original post by the author.

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Total votes 1: ↑1 and ↓0 +1
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