Jiaxin Qiu (jxqiu77)

jxqiu77

Geek Repo

Company:The University of Hong Kong

Location:China

Home Page:jxqiu77.github.io

Github PK Tool:Github PK Tool

Jiaxin Qiu's starred repositories

qBittorrent-Enhanced-Edition

[Unofficial] qBittorrent Enhanced, based on qBittorrent

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Flux-Y-Beamer

Beamer template based on Flux-beamer

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ashleymavericks

:octocat: Config for my GitHub profile

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nerd-fonts-installer

Nerd Fonts Installer is a bash script that allows users to easily install any nerd font in a Debian-based distribution by following a few simple steps.

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github-readme-activity-graph

A dynamically generated activity graph to show your GitHub activities of last 31 days.

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github-profile-3d-contrib

This GitHub Action creates a GitHub contribution calendar on a 3D profile image.

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awesome-github-profile-readme

😎 A curated list of awesome GitHub Profile which updates in real time

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DataScienceInteractivePython

Python interactive dashboards for learning data science

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lazygit

simple terminal UI for git commands

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the-art-of-command-line

Master the command line, in one page

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Linear-Algebra-Left-Undone

线性代数:未竟之美

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stat-ml-edu

Resources for education in statistics and machine learning: from advanced undergraduate to research level

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GuaranteeML

ETH Guarantees for Machine Learning

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mtheme

A modern LaTeX Beamer theme

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minted

minted is a LaTeX package that provides syntax highlighting using the Pygments library. Highlighted source code can be customized using fancyvrb.

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dowww

📟 Dev on Windows with WSL | 在 Windows 上用 WSL 优雅开发

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RandomMatrix.jl

A package for Random Matrix Theory

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github-emoji-picker

A simple emotion picker that displays all the supported GitHub emojis :octocat:.

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al-folio

A beautiful, simple, clean, and responsive Jekyll theme for academics

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SciMLBook

Parallel Computing and Scientific Machine Learning (SciML): Methods and Applications (MIT 18.337J/6.338J)

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tutorials

This is the official repository for the "doggo dot jl" YouTube channel (fka "julia for talented amateurs").

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Rfast

A collection of Rfast functions for data analysis. Note 1: The vast majority of the functions accept matrices only, not data.frames. Note 2: Do not have matrices or vectors with have missing data (i.e NAs). We do no check about them and C++ internally transforms them into zeros (0), so you may get wrong results. Note 3: In general, make sure you give the correct input, in order to get the correct output. We do no checks and this is one of the many reasons we are fast.

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statistical-learning-method-solutions-manual

统计学习方法习题解答,在线阅读地址:https://datawhalechina.github.io/statistical-learning-method-solutions-manual

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install-latex-guide-zh-cn

一份简短的关于 LaTeX 安装的介绍

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tibbles-group

Resources for Ryan Tibshirani's research group

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convexopt-book1

Convex optimization for statistics and machine learning

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