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license: apache-2.0
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## 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](http://www.cs.cmu.edu/~tom/mlbook.html)): 25 pages of notes
- Statistics: 9 cheatsheets
- Deep Learning: 12 cheatsheets, will upload more
- Image Processing (follows [digital image processing book](https://www.amazon.fr/Digital-Image-Processing-Rafael-Gonzalez/dp/013168728X)): 21 cheatsheets
- Data Structures and Algorithms (follows [this book by Goodrich](https://www.wiley.com/en-us/Data+Structures+and+Algorithms+in+Python-p-9781118549582)): 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.
- I will upload more notes as I find or create them. Will soon compile my Hugging Face cheatsheets so stay tuned!
- It's appreciated if you could improve the quality of PDF handwritten scans or convert them to JPEG, you can open a PR to this repository.


*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 PDF`s.
- I uploaded Hugging Face cheatsheets.