My small cheatsheets for data science, ML, computer science and more.
My Notes 📓
This repository contains my lecture notes from graduate school on following topics 👇🏼
Data Science: 8 cheatsheets
Machine Learning (follows Tom Mitchell's book): 25 pages of notes
Statistics: 9 cheatsheets
Deep Learning: 12 cheatsheets, will upload more
Image Processing (follows digital image processing book): 21 cheatsheets
Data Structures and Algorithms (follows this book by Goodrich): 26 cheatsheets
✨Some notes✨
Most of these notes aren't intended to teach a topic from scratch but are rather notes that I took and compiled during my midterm & finals, might help you remember things, study for exams, and prepare for job interviews.
There might be very small Turkish notes in few of the pages, you can ignore them. One or two of the pages might be not good visually.
If you can improve the quality of handwritten notes or convert PDFs to JPEG, feel free to open a PR. (it's appreciated)
I will upload more notes as I find or create them. Will soon compile my Hugging Face cheatsheets so stay tuned!
Updates🎉
I uploaded hierarchical clustering and improved version of K-means.
I compiled every lecture in separate PDFs, and also compiled those into single PDF, found under Compiled PDFs in HF repository(GitHub doesn't accept big files).