The most important application for decomposition is in data fitting. The following discussion is mostly presented in terms of different methods of decomposition for linear function.

Determinants are mathematical objects which have applications in engineering mathematics. For example, they can be used in the solution of simultaneous equations, and to evaluate vector products. Determinants can also be used to see if a system of $n$ linear equations in $n$ variables has a unique solution. There are several ways to calculate determinant, however, today I'm going to introduce another way of computing determinants Chio Identity.

This is actually one of my project when I was in college during my "Mathematical Programming" class. I used R programming language to solve missionaries and cannibals problem with matrix analysis and graph theory.

Web search engines such as Google.com distinguish themselves by the qualtiy of their returns to search queries. I will discuss a rough approximation of Google's method for judging the qualtiy of web pages by using PageRank.

The ability to classify music in an automated manner has become increasingly more important with the advent of musical streaming services allowing greater access to music. Spotify alone hit 100 million users in 2016, with other services provided by companies such as Apple, Soundcloud and YouTube. In addition, there are huge numbers of professional musicians, approximately 53,000 in the USA alone, as well as amateurs who are producing music which needs to be classified. With this quantity of music, it is unfeasible to classify genres without an automated method.

Today I'm going to summarise some important point about weighted word embedding for some specific NLP tasks. Frankly speaking, this is the topic I wish to write about a few months ago, however, I was so busy during my MSc.

A web crawler, sometimes called a spiderbot or scraper, is an internet bot that systematically browses the net. We can get the information we need without copy-paste. The goal of this article is to let you know how I scrape web and store it into database or csv file.

In this article, I'm going to build my own pre-trained word embedding on WSL, which stands for Windows Subsystem for Linux, and it is a compatibility layer for running Linux binary executables (in ELF format) natively on Windows 10.. The reason why I train the model on Linux instead of Windows is that it's not user-freiendly to run C++ and some other packages on Windows.