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).