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).
• I uploaded Hugging Face cheatsheets.