This is a new and improved version of my knowledge base, with more robust backlinks.

Here is how I'll break everything down:

• [[Statistics| Statistics]] - focuses on [[Probability]], [[Distributions]], [[Hypothesis tests]], some [[Bayesian statistics]], and [[Linear Regression Derivation and Assumptions|Linear Regression]]. This is largely where all the math-heavy bits go, any modeling beyond linear regression is going in the data science bucket.
• [[Data Science and Machine Learning|Data Science and Machine Learning]] - focuses on what I call [[Classical machine learning models|Classical machine learning models]] (i.e. all the models that you learn about in an intro to data science class) plus [[Neural Networks|Neural Networks]]
• [[Physics|Physics]] - Divided into 3 sections: [[Physics 1 - Summary|Physics 1]] for mechanics, [[Physics 2 - Summary|Physics 2]] for E&M, and [[Other topics|Other topics]] for things like [[Waves]], [[Thermodynamics]] , and [[Optics]], which are sometimes include in physics 1 or 2 depending on the school / course. If I ever get the time I'll start populating some more advanced topics, like [[Quantum Mechanics]] or more advanced deep dives into [[Thermodynamics - Header|Thermodynamics]] and [[E&M - Header|E&M]], but that won't be in the near future.
• [[Math|Math]] - Captures [[Algebra|Algebra]], [[Trigonometry|Trigonometry]], [[Geometry|Geometry]], [[Calculus 1|Calculus 1]], and [[Calculus 2|Calculus 2]]. Most of these come from old tutoring sessions, so some topics are covered pretty comprehensively but there will be lots of gaps. My focus in the near future is on [[Graph Theory|Graph Theory]] and [[Modern Algebra|Modern Algebra]] since it ties in with some personal programming projects and my own interests, so the other sections in this will be pretty barren for now.