Randomness Having real randomness on a deterministic machine is a pretty interesting topic, while one can easily achieve pseudo-randomness by creating a complex algorithm with unpredictable outputs(such as a chaotic system). However, for a microcontroller with the same code whenever it boots up, the above solution will give you the same number every time. So it would be nice to introduce some...

## Generative Adversarial Networks and Game Theory

GAN(Generative Adversarial Network) is a Neural Network model in which there exist two neural networks, one commonly referred to be the Generator and the other as Discriminator. Adversarial Learning is a study of attacking neural networks, but it is being used as a tool to build the GAN model. In each iteration, the Generator will synthesize a product–commonly to be images in modern...

## CMake vs. Make

What was the Problem? :() When playing with my RP2040, following the official SDK instructions, I wonder why I have to type cmake then do make, why does it take two steps to build my project? Well, long story short: Cmake is a cross-platform Makefiles generator, while make “reads the makefile and invokes a compiler, linker, and possibly other programs to make an executable file...

## Bare Metal WebServer On Pi PicoW

Intro I’ve been pretty into the Raspberry Pi Pico family lately—it looks nice, and it’s new, there is a fast-growing community there, and it would be cool to play together. Pico W is the newer member with the…well, you guess…the Wireless capability. I thought it would be nice to set up some code to allow me to send data from the terminal to the Pico through wifi...

## FAMA 70 Factor Model using Modern MachineLearning Techniques

## Machine Learning Notes III

*This note is still open Machine Learning Notes I Machine Learning Notes II The Primal Question of Optimization For a general optimization problem, it usually could be rewritten as maximizing or minimizing a certain function with several constrictions. For example, maybe you want the optimized value non-negative. The most basic form of such is called the primal question which looks like this: And...

## Machine Learning Notes II

Link to Machine Learning Notes I The least squares estimates of α and β For simple linear regression: we have: Linear Regression way We can all use the NN method to solve the regression problem but that leads to being nearly impossible to locate exactly which layer foreshadows which feature of the data. Thus, maybe the better way is to upscale the dimension of the linear regression method. That...

## Bayes’ Rule

When I was in the high school learning about AP statistics I learned the formula: , Which able to be transformed as: is called “Conditional probability” which pretty much self-explained itself. For which I only knew the meaning of each element but not the whole idea, what I do is just plug in numbers, because it is kinda abstract to understand from itself: “The probability of...

## Machine Learning Notes I

Lately, I was into the studying process of machine learning, and outputting(taking notes) is a vital step of it. Here, I am using Andrew Ng’s Stanford Machine Learning course in Coursera with the language of MATLAB. So the rest of the code I will write in this post by default are based on MATLAB. What is ML? “A computer program is said to learn from experience E with respect to some...