Singular Value Decomposition (SVD) is a widely used technique to decompose a matrix into several component matrices, exposing many of the useful and interesting properties of the original matrix.

In this article, first, I'll populate crypto database using Python and SQL. I retrieve the list of crypto coin assets, verify the data, and tackle any errors I encounter along the way. Second, I'll talk about how to keep the database up to date with the latest prices, and retrieve daily data from the yahoo finance API. Third, a database for twitter data will be built as well. Finally, I'll set up to build a web UI using FastAPI.

Time series prediction has been widely applied to the finance industry in applications such as stock market price and commodity price forecasting. Machine learning methods have been widely used in financial time series prediction in recent years. How to label financial time series data to determine the prediction accuracy of machine learning models and subsequently determine final investment returns is a hot topic.

This article is about implementing "Eigenvectors from eigenvalues" of Terence Tao's paper using Python and R. It's a amazing work and mathematics contribution from Terence Tao. It is an elegant non-evident result, which makes me so excited about it!

Happy π Day 2021! In this article I'll estimate the digits of π with random numbers and the probability of two integers being co-prime. What is the probability of two random integers being coprime? Euclidean Algorithm can be used to estimate π!

Principal Component Analysis (PCA) is an important technique to understand in the fields of statistics and data science. It is a process of computing the principal components and utilising then to perform a change of basis on the data. For the purpose of visualisation, it is very hard to visulaise and understand the data in high dimensions, this is where PCA comes to the rescue.

In Data Science interviews, one of the frequently asked questions is 'What is P-Value?'. It's hard to grasp the concept behind p-value. To understand p-value, you need to understand some background and context behind it.

When I was doing my dissertation project, I found out that the performance of model wasn't quite well. I believe it's because the domain of pre-trained GoogleNews-vectors-negative300 is different from the the dataset of mine. Hence, I decide to pre-train a word2vec model by myself.

The objective of this task is to detect hate speech in tweets. For the sake of simplicity, let's say a tweet contains hate speech if it has a racist or sexist sentiment associated with it. So, the task is to classify racist or sexist tweets from other tweets.

Google Colab notebooks have an idle timeout of 90 minutes and absolute timeout of 12 hours. This means, if user does not interact with his Google Colab notebook for more than 90 minutes, its instance is automatically terminated. Also, maximum lifetime of a Colab instance is 12 hours.

Sometimes the code I write may not work in my local machine, however, it works in Google Colab. So, I wanna connect to Google Colab terminal using SSH.

Visualizing sound is kind of a trippy concept. There are some mesmerizing ways to do that, and also more mathematical ones, which I will explore both in this article.

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.