Jayoon

Jayoon's Stars

• Asabeneh/30-Days-Of-Python

  30 days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than100 days, follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

  Language:Python43.6k8261398.3k

• donnemartin/interactive-coding-challenges

  120+ interactive Python coding interview challenges (algorithms and data structures). Includes Anki flashcards.

  Language:Python29.7k959684.5k

• afshinea/stanford-cs-229-machine-learning

  VIP cheatsheets for Stanford's CS 229 Machine Learning

  17.8k715274k

• FavioVazquez/ds-cheatsheets

  List of Data Science Cheatsheets to rule the world

  14.8k538173.9k

• rougier/numpy-100

  100 numpy exercises (with solutions)

  Language:Python12.3k204905.8k

• edwardtufte/tufte-css

  Style your webpage like Edward Tufte’s handouts.

  Language:HTML6k104116457

• careercup/CtCI-6th-Edition-Python

  Cracking the Coding Interview 6th Ed. Python Solutions

  Language:Python5k125431.8k

• nikitavoloboev/knowledge

  Everything I know

  Language:JavaScript4.8k12344563

• jonathan-bower/DataScienceResources

  Open Source Data Science Resources.

  4.1k40081.5k

• adnanaziz/EPIJudge

  EPI Judge - Preview Release

  Language:C++2.8k1721301.9k

• rbhatia46/Data-Science-Interview-Resources

  A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

  2.8k477671

• shervinea/mit-15-003-data-science-tools

  Study guides for MIT's 15.003 Data Science Tools

  1.8k643363

• hadley/stats337

  Readings in applied data science

  Language:R1.6k1346229

• Sroy20/machine-learning-interview-questions

  This repository is to prepare for Machine Learning interviews.

  1.5k831392

• percyliang/cs229t

  Statistical Learning Theory (CS229T) Lecture Notes

  Language:TeX719231134

• alexhagiopol/cracking-the-coding-interview

  :books: C++ and Python solutions with automated tests for Cracking the Coding Interview 6th Edition.

  Language:C++626301155

• uber-research/go-explore

  Code for Go-Explore: a New Approach for Hard-Exploration Problems

  Language:Python559191399

• youssefHosni/Efficient-Python-for-Data-Scientists

  Writing clean and optimized Python code

  Language:Jupyter Notebook537110124

• davidstutz/latex-resources

  Collection of LaTeX resources and examples.

  Language:TeX534232137

• macoj/phd

  A list of resources on how/why to do a PhD

  34813152

• KennethanCeyer/tutorial-git

  :blue_book: 어떻게 깃을 사용하는지 빠르게 알아봅시다. (Quick learn How to use Git.)

  326155126

• swcarpentry/good-enough-practices-in-scientific-computing

  Minimalist alternatives to "best practices" paper

  Language:TeX1592010623

• DavisTrey/ExperimentationResources

  A list of blogs, videos, and other content that provides advice on building experimentation and A/B testing platforms

  15211021

• jaimyoung/data-science-in-korean

  한국어를 포함한 데이터와 분석코드를 다루는 팁

  568025

• openworm/wormbrowser

  The Worm Browser -- a 3D browser of the cellular anatomy of the c. elegans

  Language:JavaScript4912312

• AstinCHOI/Python-and-Algorithms-and-Data-Structures

  ✨Algorithms & Data Structure in Python book (published by Hanbit Media, Inc.) - Python solutions for every exercises from "Cracking the Code Interview"✨

  Language:Python474037

• percyliang/refdb

  Stores paper references, outputs to bib/html, does basic sanity checking on bib entries

  Language:TeX3928025

• ecandes/stat318

  Notebooks for Stats 318

  Language:Jupyter Notebook4105