Linear Algebra (I)


When I was learning Linear Algebra in University, I found it was hard to understand what would applications of this course. I remember that we learned determinant on Chapter 1, then we learned a lot of other concept such as Rank and EigenValue. I could only memorize one after another theorems without knowing why these happened to appear this way. However, when I was learning matrices from lectures taught by Gilbert Strang, I found every conclusion is so nature that I could easily understand and associate a bunch of concepts with each other. I’d like to conclude what I had learned from him as well as hoping that someone can learn from that.


Gradient Descent in Logistic Regression

As a simple model, Logistic regression is very popular in Machine Learning, especially in computer industry while gradient descent is more of popularity as well among dozens of optimization methods. The aim of this article is to demonstrate how to reach these formulas conclusion.


Hello World

Welcome to Hexo! This is your very first post. Check documentation for more info. If you get any problems when using Hexo, you can find the answer in troubleshooting or you can ask me on GitHub.