Welcome to the neuralwiki!
Hello, my name Patrick Peng, I am the random person who started this neural-network.wiki that you are looking at right now:)
As of the time I wrote this, I am a 15-yrs-old freshman student in a high school in Avon, CT; we have a huge campus so I like riding around with my scooter (despite the fact it always gets stolen but I still love riding around the campus) (not sure why is that related). During my free time, I like to do small-tech projects that usually "sound" way cooler then they actually is, and also do cybersecurity research that I am passionate and interested in, and write fun but less professional about them (Finding bugs in Evernote and other million user apps, Supply-Chain-Attacks in python AI/ML packages, ROPing a Mips Router from scratch... ), I enjoy writing, but I love sharing:) You should take a look at them whenever you want at https://retr0.blog/blog, I can't guarantee you that you will like them, but can guarantee it's fun to read!
Speaking of things I am passionate about, my passion is to push me to start this neural-network-wiki site! But if you ask me why I am passionate about machine-learning this much, I have no idea. I was first introduced to all these astonishing AI/ML things, when I was doing threat research for a platform that allowed me to earn a bit of fortune with my cybersecurity ability, back then (even though I am still doing it now but I like to use back-then) the job needs you to jump into these large-scale open-source ML Libraries and find critical bugs in it (bugs that allowed attackers to hack you when downloading a model, inferencing with the model, or via some random endpoint your inference server opened), and when your job is to find bugs instead of appreciating the code you will find that you appreciate the code more since you can't find bugs. After working with different, tons of machine learning libraries, you will start to have a idea about what machine learning is about, how people are apply it in real-life, the more you are exposed to, the more it make you wonder how they are actually working, functioning, what's the math behind this?
I haven't learned a single bit of calculus when started to learn behind-the-scene machine learning; You can really simply imaging what it challenge it will be, I struggled with basic derivatives, power rule took me awhile, I was struggling so much that I felt like a complete-idiot... However, is these process of struggling, get me actually into calculus, and machine learning. I want to learn so bad that I arranged meeting with my coordinator 3-times and took a extra quiz to take calculus in my freshman year.
As I will like to borrow from one of my favorite math teacher from YouTube, 3blue1brown:
Inventing math is no joke, and there is a difference between being told why something makes sense and actually generating it from scratch. But at all points I want you to think to yourself if you were an early mathematician pondering these ideas and drawing the right diagrams, does it feel reasonable that you could have stumbled upon these truths yourself?
This wiki borrows alot from StatQuest, the other favorite math teacher from YouTube
As little as much this wiki can help you, I really want you to learn it by yourself instead of get anything told by me, hope you like the course, you can start now!