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.doom.d

doom-emacs private configuration

.spacemacs.d

My Emacs ( on windows ) starts here

2019-cs109a

https://harvard-iacs.github.io/2019-CS109A/

500lines

500 Lines or Less

abigsurvey

A collection of 700+ survey papers on Natural Language Processing (NLP) and Machine Learning (ML)

ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

albert

程序员实用资源

algs4

Algorithms, 4th edition textbook code and libraries

an-introduction-to-statistical-learning

This repository contains the exercises and its solution contained in the book An Introduction to Statistical Learning

an.emacs.tutorial.for.vim.user

This is an simple emacs tutorial for vim users.

awesome-chinese-llm

整理开源的中文大语言模型，以规模较小、可私有化部署、训练成本较低的模型为主，包括底座模型，垂直领域微调及应用，数据集与教程等。

awesome-chinese-nlp

A curated list of resources for Chinese NLP 中文自然语言处理相关资料

awesome-public-datasets

An awesome list of high-quality open datasets in public domains (on-going). By everyone, for everyone!

awesome-python

A curated list of awesome Python frameworks, libraries, software and resources

bayesianlearning

Bayesian Machine Learning

biopython

Official git repository for Biopython (converted from CVS)

bjguahao

北京市预约挂号统一平台脚本(Python3)

blog_comment

books

:books: Books worth reading

byte-of-python

A Byte of Python book

chinese-poetry

最全中华古诗词数据库, 唐宋两朝近一万四千古诗人, 接近5.5万首唐诗加26万宋诗. 两宋时期1564位词人，21050首词。

coldnew-spacemacs

My spacemacs config (based on coldnew-emacs)

config

My config for gentoo linux, xmonad, vim, emacs, git, mutt, newsbeuter, tmux, pentadactyl, npm, idesk, xbindkeys, ...

content

Official content for Harvard CS109

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

cs-book

计算机类常用电子书整理，并且附带下载链接，包括Java，Python，Linux，Go，C，C++，数据结构与算法，人工智能，计算机基础，面试，设计模式，数据库，前端等书籍

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

cs224n-winter-2017

All lecture notes, slides and assignments from CS224n: Natural Language Processing with Deep Learning class by Stanford

cs231n.github.io

Public facing notes page

d2l-en

Dive into Deep Learning, Berkeley STAT 157 (Spring 2019) textbook. With code, math, and discussions.