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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): 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.
• 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 PDFs.
• I uploaded Hugging Face cheatsheets.