└── README.md /README.md: -------------------------------------------------------------------------------- 1 | # Awesome-AI-algorithm 2 | 3 | > 人工智能算法方面的综合资料合集:包括求职面试、机器学习、深度学习、强化学习等方面的资料和代码（持续更新中） 4 | > 近期将更新一大波互联网大厂实习内推、校招相关信息（敬请关注！） 5 | 6 | [![GitHub stars](https://img.shields.io/github/stars/murufeng/Awesome-AI-algorithm.svg?style=social&label=Stars)](https://github.com/murufeng/Awesome-AI-algorithm) [![GitHub forks](https://img.shields.io/github/forks/murufeng/Awesome-AI-algorithm.svg?style=social&label=Forks)](https://github.com/murufeng/Awesome-AI-algorithm) [![HitCount](http://hits.dwyl.io/murufeng/Awesome-AI-algorithm.svg)](http://hits.dwyl.io/murufeng/Awesome-AI-algorithm) 7 | 8 | ## 资料目录 9 | - **大厂内推：实习/春招/社招** 10 | - [微软--自然语言处理实验室(招聘科研实习生)](https://mp.weixin.qq.com/s/VFS3suol7Rph7SFGVO24QA) 11 | - [算法面试](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#Algorithm-Interview) 12 | - [Github](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#1-github) 13 | - [牛客网](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#2-nowcoder) 14 | - [知乎](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#3-zhihu) 15 | - [博客](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#4-blog) 16 | - [微信公众号](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#5-wechat) 17 | - [其它](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#6-others) 18 | - [机器学习](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#machine-learning) 19 | - [面试](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#1-interview) 20 | - [资料](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#2-documentation) 21 | - [Github代码](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#3-Coding) 22 | - [深度学习](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#deep-learning) 23 | - [面试](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#1-interview-1) 24 | - [资料](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#2-documentation-1) 25 | - [课程](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#3-course-1) 26 | - [强化学习](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#Reinforcement-Learning) 27 | - [资料](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#1-Documentation) 28 | - [论文](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#2-papers-and-algorithm) 29 | - [课程](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#3-Course-and-Code) 30 | - [C/C++](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#cc) 31 | - [Python](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#python) 32 | - [Pytorch](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#pytorch) 33 | - [TensorFlow](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#tensorflow) 34 | - [竞赛/比赛平台](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#competition) 35 | - [其他](https://github.com/murufeng/Awesome-AI-algorithm/blob/master/README.md#others) 36 | --- 37 | --- 38 | 39 | ## Algorithm Interview 40 | ### 1. Github 41 | - 2020算法工程师面试题汇总 [website](http://bbs.cvmart.net/topics/1038) 42 | - 2020年的算法实习岗位信息表，部分包括内推码，和常见深度学习算法岗面试题及答案，暑期计算机视觉实习面经和总结 [Github](https://github.com/HarleysZhang/2019_algorithm_intern_information) 43 | - 2019年最新总结，阿里，腾讯，百度，美团，头条等技术面试题目，以及答案 [Github](https://github.com/murufeng/interview_internal_reference) 44 | - 算法工程师面试 [Github](https://github.com/PPshrimpGo/AIinterview) 45 | - 算法/深度学习/NLP面试笔记 [Github](https://github.com/imhuay/Algorithm_Interview_Notes-Chinese) 46 | - 2019届秋招面经集合 [Github](https://github.com/zslomo/2019-Autumn-recruitment-experience) 47 | - 技术面试必备基础知识 [Github](https://github.com/CyC2018/CS-Notes) 48 | - 阿里、腾讯、百度、华为、京东、搜狗和滴滴最新面试题汇集 [Github](https://github.com/xiaole0310/interview-) 49 | - 「面试算法练级攻略」-「LeetCode题解」-「剑指offer题解」 [Github](https://github.com/guokaide/algorithm) 50 | - MVision-awesome [Github](https://github.com/Ewenwan/MVision) 51 | - Daily Interview [Github](https://github.com/datawhalechina/Daily-interview) 52 | - 2019年最新总结，阿里，腾讯，百度，美团，头条等技术面试题目，以及答案，专家出题人分析汇总 [Github](https://github.com/0voice/interview_internal_reference) 53 | - CV岗常见面试题 [Github](https://github.com/donnyyou/cv-interview) 54 | 55 | 56 | ### 2. Nowcoder 57 | - 2020届计算机视觉实习生面试经验（腾讯/头条/商汤/旷视/达摩院等） [nowcoder](https://www.nowcoder.com/discuss/159266) 58 | - 20届-视觉算法-暑期实习 [nowcoder](https://www.nowcoder.com/discuss/173292) 59 | - 面经（腾讯AI Lab，阿里达摩院，华为等公司大集合） [nowcoder](https://www.nowcoder.com/discuss/180087) 60 | - 字节跳动实习算法岗面经 [nowcoder](https://www.nowcoder.com/discuss/174565) 61 | - 阿里腾讯虎牙机器学习算法面经 [nowcoder](https://www.nowcoder.com/discuss/175759) 62 | - 字节跳动图形图像算法实习面经 [nowcoder](https://www.nowcoder.com/discuss/178153) 63 | - 拼多多算法实习生面经 [nowcoder](https://www.nowcoder.com/discuss/177911) 64 | - 算法岗面经传送门 [nowcoder](https://www.nowcoder.com/discuss/180976) 65 | - 面经（腾讯AI Lab，阿里达摩院，华为等公司大集合） [nowcoder](https://www.nowcoder.com/discuss/180087) 66 | - cv岗面经 [nowcoder](https://www.nowcoder.com/discuss/159266) 67 | - 小菜鸡的算法实习面经 [nowcoder](https://www.nowcoder.com/discuss/181770) 68 | - 机器学习/算法校招面试考点汇总 [nowcoder](https://www.nowcoder.com/discuss/165930) 69 | - 计算机视觉暑期实习面经 [nowcoder](https://www.nowcoder.com/discuss/186000) 70 | - 面经 | 商汤科技计算机视觉岗【二面】 [nowcoder](https://www.nowcoder.com/discuss/267852) 71 | - 面经 | 阿里巴巴达摩院 CV 四轮算法面经 [nowcoder](https://www.nowcoder.com/discuss/216797) 72 | - 面经 | 百度、美团、拼多多、寒武纪等互联网大厂面试经验 [nowcoder](https://www.nowcoder.com/discuss/241988) 73 | - 面经 | 旷视科技算法研究员面经 [nowcoder](https://www.nowcoder.com/discuss/167336) 74 | - 算法面经 | 微软/阿里/百度/字节跳动/华为/OPPO [nowcoder](https://www.nowcoder.com/discuss/181117) 75 | - 旷视19届春招-算法研究员-凉经 [nowcoder](https://www.nowcoder.com/discuss/167336) 76 | - 腾讯算法实习面试总结 [nowcoder](https://www.nowcoder.com/discuss/163996) 77 | - 春招详细算法面经(旷视/海康/联影等8家公司Offer) [nowcoder](https://www.nowcoder.com/discuss/163388) 78 | - 普通的算法/机器学习面经 [nowcoder](https://www.nowcoder.com/discuss/61907) 79 | 80 | 81 | ### 3. Zhihu 82 | - 互联网公司最常见的面试算法题有哪些？ [zhihu](https://www.zhihu.com/question/24964987/answer/586425979) 83 | - 算法工程师必须要知道的面试技能雷达图 [zhihu](https://zhuanlan.zhihu.com/p/54089811) 84 | - 字节跳动计算机视觉算法实习生视频面试 [zhihu](https://zhuanlan.zhihu.com/p/59270912) 85 | - 2019秋招算法面经 [zhihu](https://zhuanlan.zhihu.com/p/42936891) 86 | - CVTE视觉计算岗实习面经 [zhihu](https://zhuanlan.zhihu.com/p/59223324) 87 | - 校招-基础算法图像处理算法 [zhihu](https://zhuanlan.zhihu.com/p/80887909) 88 | 89 | ### 4. Blog 90 | - AI算法工程师手册 [Blog](http://www.huaxiaozhuan.com/) 91 | - 小米面试总结 [Blog](https://wx.qnmlgb.tech/articles/5c55c999ce56ab804b1526cd/) 92 | - 百度/商汤AI面试 [CSDN](https://blog.csdn.net/emma1222/article/details/86551435) 93 | - 算法校招经验总结(百度,阿里巴巴,腾讯,今日头条) [CSDN](https://blog.csdn.net/ML_SDD/article/details/84986528) 94 | - CV计算机论文速览 [CSDN](https://me.csdn.net/u014636245) 95 | - 海外小硕的国内面试经历 [CSDN](https://blog.csdn.net/emma1222/article/details/86551435) 96 | - 致未来的算法工程师-算法校招经验总结（百度，阿里巴巴，腾讯，今日头条） [CSDN](https://blog.csdn.net/ML_SDD/article/details/84986528) 97 | - AI 研习社职荐专区 [AI求职百题斩](https://www.yanxishe.com/blogDetail/14457) [面经](https://www.yanxishe.com/blogDetail/14456) [website](https://job.yanxishe.com/) 98 | - 算法与数据结构、机器学习、深度学习 [Blog](https://www.liwei.party/) 99 | 100 | ### 5. WeChat 101 | - 2020 AI算法岗春招汇总 & 面经大全来了！！！ [website](https://mp.weixin.qq.com/s?__biz=MzU2NDExMzE5Nw==&mid=2247484630&idx=1&sn=29574cff482c2b90bd48f3000a1bb390&chksm=fc4ebe94cb3937821bc2c56583a0ca0f8154e1fb4b06a3b409a79752f7ccbe2dbcb23d634f29&token=336629150&lang=zh_CN#rd) 102 | - 1000 面试题，BAT 机器学习面试刷题宝典！ [website](https://mp.weixin.qq.com/s?__biz=MzU0OTU5OTI4MA==&mid=2247486469&idx=2&sn=14b701639794e67cc63bedea8d2870cb&chksm=fbac2d5accdba44c4930c42ee7c191d0a166c3b3cc8c5e2fa3efe6ed26a992b0cb6283a8114c&scene=0&xtrack=1&key=5121627df01c7147226b38275cec75014ec9b754942505b403947722cb8b7aea53b720546e71ea5d22312783c452de71448362f615081904c0c79cd401fb35fc5334f2a30b4f1ca1a7ddc764eea39116&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060739&lang=zh_CN&pass_ticket=UT934CWNmZoDZ1lVhvHOGEFisJUlIxDGPpY73e7nut1e18SYmUgrBd5XY3S4u28F) 103 | - 数据科学&机器学习基础面试题 [website](https://mp.weixin.qq.com/s?__biz=MzIyNjM2MzQyNg==&mid=2247484547&idx=2&sn=1f9cfeee41f80623edc493d293d4e1b8&chksm=e870d5cedf075cd886afbee37b79c85dce16f5ae43d300331c5f29e0d64c32b030b621beddaa&scene=0&xtrack=1&key=96e38258b65ecb9b9b652831c3f84574b2f25e7020610c534b933a65b3b61a0cd4a0db2b54d14a128c5e7e8136e59893ae61ee9c06580040a3c7fab669f919f48e749ca1d0f8be9f7295ffed179a4acc&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060739&lang=zh_CN&pass_ticket=M%2Bx4I8699jpuE4n781eOB5axXkLS0Mu7Zrtx6Vi8JsVQhUxr6%2F6aCUmOC8WZybav) 104 | - 阿里巴巴计算机视觉算法实习生视频面试 [website](https://mp.weixin.qq.com/s?__biz=MzUxNjcxMjQxNg==&mid=2247488083&idx=3&sn=499149282d197c1b68d3fa105a69e271&chksm=f9a260dcced5e9ca7a86741c90b5199251b4bf02b2279b314fa3302911b8d0c22e036dd7bb33&scene=21#wechat_redirect) 105 | - 面试经验AI算法工程师(面试官角度) [website](https://mp.weixin.qq.com/s?__biz=MzUxNjcxMjQxNg==&mid=2247487216&idx=1&sn=4516fd92ecd48cebb91629a0b1f3473d&chksm=f9a27c7fced5f5694608c40a8f4dce2636986d28145f073d2d8de088dd5ef3caa66423773787&scene=21#wechat_redirect) 106 | - 从零基础到BAT算法岗SP——秋招准备攻略 [website](https://mp.weixin.qq.com/s?__biz=MzUxNjcxMjQxNg==&mid=2247485936&idx=1&sn=0e156832abdc9bfd4ee82b9b70063b3e&chksm=f9a27b7fced5f26912dd64b3c6f5a2d153068843cce378a8894ffb0ea786bcba698ef0d747f3&scene=21#wechat_redirect) 107 | - 蚂蚁金服/旷视/虹软/腾讯优图暑期实习offer面经 [website](https://mp.weixin.qq.com/s?__biz=MzI4MDYzNzg4Mw==&mid=2247489199&idx=3&sn=4b1f2f5033929491f56bebbc73a63e63&chksm=ebb42e7bdcc3a76d0c2c9d98f275882b9cbf852c2f32d5ab3977a670690c1150a3ab0b04aa53&scene=0&xtrack=1&key=5aa6b6fc7e8425bd24f718156836dc2e81e8283eeb1653306993c9c6816f5ba1d0415a3a95b30fdb1daf045964002a34ccb8a4f35727519df9aea73b6b87f702d2c2b2549c21f6e5360bf6929136fc5b&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060739&lang=zh_CN&pass_ticket=ESuAgyeBfQrIeEX8gTsQm4%2BCbjzCr74m7714n%2BShviVnNifUDKpDRrHljFR6o7iD) 108 | - 机器学习与深度学习常见面试题（上） [website](https://mp.weixin.qq.com/s?__biz=MzUxNjcxMjQxNg==&mid=2247488694&idx=1&sn=167b8b9897165d3dcb285ffd12ff7aef&chksm=f9a26639ced5ef2ff2317437f5e4bd99ca8ed5d63378df591c8d654656bb7e2e8b262406d746&mpshare=1&scene=24&srcid=0428SfDKuYmDLZAmwecrlang&key=9a1004c4c06b26acf767311bd48d12abe9c4f22d623717fdf4c7c360532478e73b3c6283e549b97aba7f87bddf518c1e273bc4148f28ed46714e24760a11a2f57aaa6d36454cd29c631c5d0b21d298c0&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060739&lang=zh_CN&pass_ticket=iqu0jGzZHsjPTDJlLkm0O7uj41FuEikyiBNBZJTYuu65wgzAYk%2Bp3HNofRkaEx1J) 109 | - 机器学习与深度学习常见面试题（下） [website](https://mp.weixin.qq.com/s?__biz=MzUxNjcxMjQxNg==&mid=2247488889&idx=1&sn=ac728edf471bcd01e62132f930b14ee3&chksm=f9a267f6ced5eee02d48255208056e2c21b6403a9b00e7ae197b7d3c85e2862a6e607009bc99&scene=0&xtrack=1&key=f7bb43d4492422e0ae8fea0c881639406030f4097e3d118f315e35dcc3e33a7658535cf021dfaf606112db121d98695883fc1bc96e0f411e30e2245ebc95c6a659fa8cf4395fab1cd78593f782063cf8&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060739&lang=zh_CN&pass_ticket=iqu0jGzZHsjPTDJlLkm0O7uj41FuEikyiBNBZJTYuu65wgzAYk%2Bp3HNofRkaEx1J) 110 | - 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秋招经历（已收到百度、阿里、腾讯、美团、京东、拼多多的 offer） [website](https://mp.weixin.qq.com/s?__biz=MzIwODI2NDkxNQ==&mid=2247484467&idx=1&sn=4e4ea07d5daa4491c47623ccae364053&chksm=97048f8fa07306991c41e1b36c241e66cfe329793b3868abf9b69c9f6c8e22ed65ccdc81050b&scene=0&xtrack=1&key=f3b89a09cde51f0f18b12ad73080cb4476e44408f3adf8bf3dcb0a444d2394a43bc4d562865cb056402b1336a61cfbf2bedfce5c082867a1dfc3415eb9843d71537a4d52657e975c9a6d634e95a5acb8&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060841&lang=zh_CN&pass_ticket=RpJWE06PIp32SBXL8%2FeBcKde4wI7jAKOPyofLWQB%2FfLrZ2GcooZxvXB2E1yAZax7) 120 | - 10大机器学习Q&A，面试必知！ [website](https://mp.weixin.qq.com/s?__biz=MzUxNjcxMjQxNg==&mid=2247491786&idx=4&sn=0b90f86f56cdee3ca6d521ba5daa431d&chksm=f9a19245ced61b53843fd0ebce665682e1f32ba783a53047ada8588996544053282d7988ccd0&scene=0&xtrack=1&key=a4f2e1c5351761187f5a6ed4c82f78256be962afa2035410b0c853353d63912b5bb6ba70dbfba485d77a657e724808eebc40721de0069b67d3a8e55379ab42898bfae411820edf36cc4d2128efd7133d&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060841&lang=zh_CN&pass_ticket=qYkZjE2bwZNl6kCdiw9%2FVQhvf4pr95lZY5htRdH4dZlMmAkwLaO37AuuvCezNz0w) 121 | - 机器学习常见算法优缺点总结！ [website](https://mp.weixin.qq.com/s?__biz=MzI1MzY0MzE4Mg==&mid=2247485383&idx=1&sn=dc481b7e6261aecfada7b772fd2ae471&chksm=e9d01706dea79e1097a39ee0779dd8ab99671714f177133fc9f4dbd531e0cee4807cd34f178c&scene=0&xtrack=1&key=d5739ef05bcda6301af88ca81d2856a4296b48c7e05d1733f3d195063ccd566c1430c6d2cbf990173ec038c842d0b8c710678815b45174cb508e0e6c80e5d48790e062a492ef85b13f3b9a4d2b644b77&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060841&lang=zh_CN&pass_ticket=CqBupw%2FP1tVbatYy5KtWCuDWZ2meT4iMIDhjMVNgyWAou9uxB8EDLiHzBzTHh2xj) 122 | - 2019秋招AI算法岗复盘 [website](https://mp.weixin.qq.com/s?__biz=MzIxOTczOTM4NA==&mid=2247488788&idx=2&sn=50116b5ec4c9171b49bb52d36386a9ff&chksm=97d7f083a0a079952bdb093250f6ee01a15434ba5b3f7d8ae038cba23a7c28315d331a0ceedd&scene=0&xtrack=1&key=a4f2e1c535176118d1a03004f064566b9a1952a6fada428118cb08d353feab39102f225cb6fff0f98cf55790d9d3a589ea653a270e5e6e89407c726a2c3483a980cbbbda8890a3cecfe24fd88348e1ca&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060841&lang=zh_CN&pass_ticket=e6hh0zbWeUNXFGwXBwcggQr95dIdog5Q1MWep%2FM9ahanjOPwIheztFnowX0pNCPE) 123 | - 秋招面验 | 计算机视觉汇总面经分享 [website](https://mp.weixin.qq.com/s?__biz=MzI5MDUyMDIxNA==&mid=2247491490&idx=2&sn=cd09d4186254d18aef769fc634d68e86&chksm=ec1ff25bdb687b4de2e46645891760f19637bb9a357d07aa72fb61ada483cf486c5a1e352170&scene=0&xtrack=1&key=a4f2e1c5351761188e9e953dfd54a925f5b9cd52bc369cbfb582cfb4f749c6ee2aa611832c4d2b714b81a6b4abc9ac8bc737eb46c8128f157660d2d23f2bf176c051a2e972f10b346884e58009985fa7&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060841&lang=zh_CN&pass_ticket=e6hh0zbWeUNXFGwXBwcggQr95dIdog5Q1MWep%2FM9ahanjOPwIheztFnowX0pNCPE) 124 | - 面试官比较看重简历中的哪些维度，有什么写简历的技巧、建议和总结？ [website](https://mp.weixin.qq.com/s?__biz=MzIyNjM2MzQyNg==&mid=2247487038&idx=1&sn=0ac71c12bd7d54a9a52b5e97a9622fe6&chksm=e870df73df075665392ddced32243db8058297e2d0d67e757aac9adec8f5dd2dbe4d1f7c0523&mpshare=1&scene=1&srcid=&sharer_sharetime=1573355519003&sharer_shareid=8724c7983f20914ec3c0c086bba89335&key=d4e2e0a334fd7fc709362ca1227355bf6c28c5babea298ca5610006e4c4531543ae1a28be050456a55c994a46bd6e4895aa6643190377fc359e04dae87a37272a4112e7552e8bcaedd60bfa1b01539f6&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62070152&lang=zh_CN&pass_ticket=bKjcsGTk1thGyRHccXtSB6iwtrQWAI3mkAWK%2FFUqE6qp4dWMipHk2gUW9BhzyLCY) 125 | 126 | 127 | ### 6. Others 128 | - Solutions to Introduction to Algorithms [Github](https://github.com/gzc/CLRS) 129 | - CV 领域论文常见单词 [zhihu](https://zhuanlan.zhihu.com/p/60049093) 130 | - CV 领域Paper论文常见单词 [zhihu](https://zhuanlan.zhihu.com/p/58860096) 131 | --- 132 | 133 | ## Machine Learning 134 | ### 1. Interview 135 | - machine-learning-interview-questions [Github](https://github.com/Sroy20/machine-learning-interview-questions) 136 | - 机器学习与深度学习面试问题总结 [Blog](https://mp.weixin.qq.com/s?__biz=MzIxODM4MjA5MA==&mid=2247486331&idx=1&sn=abc69ee44d932dd7d6bc4bbef82045c8&chksm=97ea211ea09da808a546c4a6f485f45289fea2e69cddc95aaf16f06ddfb9c428ecf9d259c980&scene=0&key=f7bb43d4492422e0472e06f4faf0076f9d9de975e8a73050e15cd63f1f549a060f9018009aa9f1f5f19aa37f1408ecb3ea2be5b8464b4eae89884e1d881c91ebef20c84ea9198fed470f36016f54c30a&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62060739&lang=zh_CN&pass_ticket=fLkIwHFJHv2%2FbP8RGzzYjXOZFDZBSwG0jwcmIEQhVi6CQoLDsa0PiCF8xoyKnPtI) 137 | - 机器学习面试复习资源 [Github](https://github.com/wangyuGithub01/Machine_Learning_Resources) 138 | - 机器学习面试算法梳理 [Blog](https://www.cnblogs.com/tornadomeet/p/3395593.html) 139 | 140 | ### 2. Documentation 141 | - 模式识别圣经-PRML(python) [Github](https://github.com/ctgk/PRML) 142 | - ML/DL学习笔记（基础+论文） [Github](https://github.com/lartpang/Machine-Deep-Learning) 143 | - 李航博士<统计学习方法>一书中所有算法python实现 [Github](https://github.com/WenDesi/lihang_book_algorithm) 144 | - <统计学习方法>第二版的代码实现 [Github](https://github.com/fengdu78/lihang-code) 145 | - <机器学习>(西瓜书)公式推导解析 [Github](https://github.com/datawhalechina/pumpkin-book) 146 | - <数据科学实战>书代码 [Github](https://github.com/oreillymedia/doing_data_science) 147 | - 机器学习实战(Python3) [Github](https://github.com/Jack-Cherish/Machine-Learning) 148 | - 吴恩达讲授的机器学习 [Coursera](https://www.coursera.org/learn/machine-learning) [163](http://open.163.com/special/opencourse/machinelearning.html) 149 | - Python3 入门机器学习 [Github](https://github.com/liuyubobobo/Play-with-Machine-Learning-Algorithms) 150 | - 李宏毅《机器学习》笔记 [Github](https://github.com/datawhalechina/leeml-notes) 151 | - 机器学习(Machine Learning) 深度学习(Deep Learning) NLP面试中常考到的知识点和代码实现 [Github](https://github.com/NLP-LOVE/ML-NLP) 152 | - 周志华《机器学习》手推笔记 [Github](https://github.com/Sophia-11/Machine-Learning-Notes) 153 | - 《Python 机器学习》 [Github](https://github.com/rasbt/python-machine-learning-book-2nd-edition) 154 | 155 | ### 3. Coding 156 | - 机器学习算法python实现 [Github](https://github.com/lawlite19/MachineLearning_Python) 157 | - 100-Days-Of-ML-Code中文版 [Github](https://github.com/MLEveryday/100-Days-Of-ML-Code) 158 | - Homemade Machine Learning [Github](https://github.com/trekhleb/homemade-machine-learning) 159 | - Python codes for common Machine Learning Algorithms [Github](https://github.com/susanli2016/Machine-Learning-with-Python) 160 | - Machine-Learning-Study-Path-March-2019 [Github](https://github.com/clone95/Machine-Learning-Study-Path-March-2019) 161 | - The best resources in Machine Learning & AI [Github](https://github.com/RemoteML/bestofml) [Website](https://bestofml.com/) 162 | - A Machine Learning Course with Python [Github](https://github.com/machinelearningmindset/machine-learning-course) 163 | - Machine learning, in numpy [Github](https://github.com/ddbourgin/numpy-ml) 164 | - A complete computer science study plan to become a software engineer. [Github](https://github.com/ddbourgin/numpy-ml) 165 | 166 | --- 167 | 168 | ## Deep Learning 169 | 170 | ### 1. Interview 171 | - 深度学习面试问题 [Github](https://github.com/elviswf/DeepLearningBookQA_cn) 172 | - 2020年的算法实习岗位信息表，部分包括内推码，和常见深度学习算法岗面试题及答案 [Github](https://github.com/HarleysZhang/2019_algorithm_intern_information) 173 | - Deep Learning Interview 深度学习面试题目汇总 [Github](https://github.com/ShanghaiTechAIClub/DLInterview) 174 | - 深度学习面试要点总结(面试题) [zhihu](https://zhuanlan.zhihu.com/p/62935978) 175 | - 自己整理的一点和深度学习相关的面试考点 [zhihu](https://zhuanlan.zhihu.com/p/48374690) 176 | 177 | ### 2. Documentation 178 | - 机器学习/计算机视觉/ NLP的论文及笔记 [Github](https://github.com/yassouali/ML_paper_notes) 179 | - 计算机视觉知识点总结 [zhihu](https://zhuanlan.zhihu.com/p/58776542) 180 | - awesome-deep-learning [Github](https://github.com/ChristosChristofidis/awesome-deep-learning) 181 | - 深度学习500问 [Github](https://github.com/scutan90/DeepLearning-500-questions) 182 | - 复旦大学邱锡鹏教授发布<神经网络与深度学习> [Github书](https://github.com/nndl/nndl.github.io) [Github示例代码](https://github.com/nndl/nndl-codes) [Github课程练习](https://github.com/nndl/exercise) 183 | - 伯克利课程 <动手学深度学习> [Github](https://github.com/d2l-ai/d2l-zh) [课程主页](http://courses.d2l.ai/berkeley-stat-157/) [bilibili](https://space.bilibili.com/209599371/channel/detail?cid=23541) [课件和习题](https://github.com/d2l-ai/berkeley-stat-157) [英文版](http://d2l.ai/) [中文版](http://zh.d2l.ai/) [PyTorch 版]( 184 | https://github.com/dsgiitr/d2l-pytorch) 185 | - <深度学习理论与实战：提高篇> [Github](http://fancyerii.github.io/2019/03/14/dl-book/) 186 | - Awesome_Computer_Vision [Github](https://github.com/ahong007007/Awesome_Computer_Vision) 187 | - Deep-Learning-Papers-Reading-Roadmap [Github](https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap) 188 | - 神经网络讲解视频 [YouTube](https://youtu.be/aircAruvnKk?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi) [bilibili](http://space.bilibili.com/88461692/#/) 189 | - 神经网络和深度学习的在线书籍 [website](http://neuralnetworksanddeeplearning.com/) [chinese](https://tigerneil.gitbooks.io/neural-networks-and-deep-learning-zh/content/) 190 | - 深度学习圣经(花书)Deep Learning 中文版 [Github](https://github.com/exacity/deeplearningbook-chinese) 191 | - Open AI Blog [website](https://blog.openai.com/) 192 | - BAIR 博客 [website](http://bair.berkeley.edu/blog/) 193 | - DeepMind 博客 [website](https://deepmind.com/blog/?category=research) 194 | - Andrej Karpathy的博客 [website](http://karpathy.github.io/) 195 | - Christopher Olah的博客 [website](http://colah.github.io/) 196 | - WildML Blog [website](http://www.wildml.com/) 197 | - Ruder的博客 [website](http://ruder.io/) 198 | - FAIR博客 [website](https://research.fb.com/blog/) 199 | - inFERENCe Blog [website](http://www.inference.vc/) 200 | - Andrew Trask的博客 [website](http://iamtrask.github.io/) 201 | - Graduate Descent Blog [website](http://timvieira.github.io/blog/) 202 | - Adit Deshpande的博客 [website](https://adeshpande3.github.io/) 203 | - createmomo的博客 [website](https://createmomo.github.io/) 204 | - 深度神经网络中的一些模型 进行统一的图示 [Github](https://github.com/weslynn/AlphaTree-graphic-deep-neural-network) 205 | - five-days deep learning [website](https://mlelarge.github.io/dataflowr-web/cea_edf_inria.html) [Github](https://github.com/mlelarge/dataflowr) 206 | - Learn_Computer_Vision [Github](https://github.com/llSourcell/Learn_Computer_Vision) 207 | - Explaining the Math of how neural networks learn [Github](https://github.com/omar-florez/scratch_mlp) 208 | - (微软) AI-神经网络基本原理简明教程 [Github](https://github.com/microsoft/ai-edu/tree/master/) 209 | - 深度学习手册 [BaiduYun](https://pan.baidu.com/s/1ew3aVZizVkPVKUFx2AtDjw) pw:dy6h 210 | - An educational resource to help anyone learn deep reinforcement learning [Github](https://github.com/openai/spinningup) 211 | - Technical Notes On Using Data Science & Artificial Intelligence [website](https://chrisalbon.com/) 212 | - 微软人工智能教育与学习共建社区 [Github](https://github.com/microsoft/ai-edu) 213 | - deep-learning-drizzle [Github](https://github.com/kmario23/deep-learning-drizzle) 214 | - pyimagesearch [Website](https://www.pyimagesearch.com/) 215 | 216 | 217 | ### 3. Course 218 | - MIT 深度学习 [Github](https://github.com/lexfridman/mit-deep-learning) 219 | - 斯坦福CS231n李飞飞计算机视觉 [网易云课堂](https://study.163.com/course/courseMain.htm?courseId=1003223001) 220 | - 统计机器学习 [网易云课堂](https://study.163.com/course/courseMain.htm?courseId=1692004) 221 | - 机器学习导论 [网易云课堂](https://study.163.com/course/courseMain.htm?courseId=1694003) 222 | - 吴恩达 深度学习工程师 [网易云课堂](https://mooc.study.163.com/smartSpec/detail/1001319001.htm) 223 | - Deep Learning: Advanced Computer Vision [udemy](https://www.udemy.com/advanced-computer-vision/) 224 | - Computer Vision Certification by State University of New York [coursera](https://www.coursera.org/specializations/computervision) 225 | - Convolutional Neural Networks [coursera](https://www.coursera.org/learn/convolutional-neural-networks) 226 | - Deep Learning and Computer Vision A-Z: OpenCV, SSD & GANs [udemy](https://www.udemy.com/course/computer-vision-a-z/) 227 | - 吴恩达的深度学习专项系列课程(Deep Learning Specialization) [Coursera](https://www.coursera.org/specializations/deep-learning) [163](https://mooc.study.163.com/smartSpec/detail/1001319001.htm/) 228 | - [CS231n](http://cs231n.stanford.edu/) 229 | - [CS224n](http://web.stanford.edu/class/cs224n/) 230 | - 斯坦福公开课程：概率和统计'Probability and Statistics' [website](https://online.stanford.edu/courses/gse-yprobstat-probability-and-statistics) 231 | - MIT公开课线性代数'Linear Algebra' [website](https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/) 232 | - Fastai推出的2019年面向程序员的深度学习实战课程'Practical Deep Learning for Coders, v3' [website](https://course.fast.ai) [website](https://www.bilibili.com/video/av41718196/) 233 | - 斯坦福机器学习课程'Machine Learning(Coursera)' [coursera](https://www.coursera.org/learn/machine-learning) 234 | - 斯坦福概率图模型专项课程'Probabilistic Graphical Models Specialization(Coursera)' [coursera](https://www.coursera.org/specializations/probabilistic-graphical-models) 235 | - DeepMind强化学习导论课程'Introduction to Reinforcement Learning' [bilibili](https://www.bilibili.com/video/av24060851/) [youtube](https://www.youtube.com/playlist?list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ) 236 | - 全栈深度学习训练营(课程视频)：为熟悉深度学习基础知识的开发人员提供的实践指导课程'Full Stack Deep Learning Bootcamp' [Github](https://github.com/full-stack-deep-learning/fsdl-text-recognizer-project) [bilibili](https://www.bilibili.com/video/av49643298) [website](https://fullstackdeeplearning.com/march2019) 237 | - 跟顶级Kagglers学习如何赢取数据科学竞赛'How to Win a Data Science Competition: Learn from Top Kagglers (Coursera)' [coursera](https://www.coursera.org/learn/competitive-data-science) 238 | - CS188伯克利<人工智能导论>课程'BerkeleyX: CS188.1x Artificial Intelligence' [bilibili](https://www.bilibili.com/video/av39489278/) [website](https://inst.eecs.berkeley.edu/~cs188/fa18/) 239 | - Fast.ai发布的课程：从零开始学深度学习'Deep Learning from the Foundations' [website](https://www.fast.ai/2019/06/28/course-p2v3/) 240 | - CS230斯坦福深度学习课程(2018 年秋)'CS230: Deep Learning | Autumn 2018' [bilibili](https://www.bilibili.com/video/av47055599/) [youtube](https://www.youtube.com/playlist?list=PLoROMvodv4rOABXSygHTsbvUz4G_YQhOb) 241 | - deeplearning.ai上线的TensorFlow实践课程'TensorFlow in Practice' [website](https://www.deeplearning.ai/tensorflow-in-practice/) 242 | - MIT的Python机器学习课程'Machine Learning with Python-From Linear Models to Deep Learning' [website](https://www.edx.org/course/machine-learning-with-python-from-linear-models-to-deep-learning) 243 | - 斯坦福CS224U自然语言理解课程'CS224U：Natural Language Understanding' [website](http://web.stanford.edu/class/cs224u/index.html) 244 | - 陈蕴侬应用深度学习'107 Spring - Applied Deep Learning, Taiwan University' [bilibili](https://www.bilibili.com/video/av46656764/) [website](https://www.csie.ntu.edu.tw/~miulab/s107-adl/) 245 | - 台大林轩田老师<机器学习基石>课程 [bilibili](https://www.bilibili.com/video/av12463015/) 246 | - 台大林轩田老师课程<机器学习技法>课程 [bilibili](https://www.bilibili.com/video/av12469267/) 247 | - NTU大学李宏毅最新机器学习课程(2019) [website](http://speech.ee.ntu.edu.tw/~tlkagk/courses_ML19.html) 248 | - UC伯克利最新深度强化学习课程 [website](http://rail.eecs.berkeley.edu/deeprlcourse/) [YouTube](https://www.youtube.com/playlist?list=PLkFD6_40KJIwhWJpGazJ9VSj9CFMkb79A) [bilibili](https://www.bilibili.com/video/av69455099/) [Github](https://github.com/berkeleydeeprlcourse/homework) 249 | - 微软-计算机视觉最佳实践、代码示例和相关文档 [Github](https://github.com/microsoft/ComputerVision) 250 | 251 | --- 252 | 253 | ## Reinforcement Learning 254 | 255 | ### 1. Documentation 256 | - reinforcement learning an introduction [Github](https://github.com/ShangtongZhang/reinforcement-learning-an-introduction) 257 | - Python强化学习实战_Sudharsan Ravichandiran [Github](https://github.com/AndyYue1893/Hands-On-Reinforcement-Learning-With-Python) 258 | - 强化学习圣经_Rich Sutton_中文书、英文电子书、代码 [Github](https://github.com/AndyYue1893/reinforcement-learning-an-introduction) 259 | - 强化学习精要_冯超 (从基础到前沿，附代码) [jd](https://item.jd.com/12344157.html) 260 | - OpenAI Spinning Up英文版、中文版 [zhihu](https://zhuanlan.zhihu.com/p/49087870) 261 | - David Silver强化学习公开课中文讲解及实践 [zhihu](https://zhuanlan.zhihu.com/reinforce) 262 | - 强化学习基础David Silver笔记（陈雄辉，南大，DiDi AI Labs）[zhihu](https://zhuanlan.zhihu.com/c_135909947) 263 | - Reinforcement Learning With Open AI TensorFlow and Keras Using Python_OpenAI(注重实战) [BaiduYun](https://pan.baidu.com/share/init?surl=nQpNbhkI-3WucSD0Mk7Qcg) [提取码](av5p) 264 | - 深度强化学习落地方法论 [zhihu](https://zhuanlan.zhihu.com/c_1186982555915599872) 265 | 266 | ### 2. Papers and Algorithm 267 | - NeuronDance [Github](https://github.com/AndyYue1893/DeepRL-1/tree/master/A-Guide-Resource-For-DeepRL) 268 | - DQN [paper](https://storage.googleapis.com/deepmind-data/assets/papers/DeepMindNature14236Paper.pdf) 269 | - DDPG [paper](http://proceedings.mlr.press/v32/silver14.pdf) 270 | - A3C [paper](https://www.researchgate.net/publication/301847678_Asynchronous_Methods_for_Deep_Reinforcement_Learning) 271 | - 清华张楚珩博士(强化学习论文汇总) [zhihu](https://zhuanlan.zhihu.com/p/46600521) 272 | - papers with code [papers](https://www.paperswithcode.com/area/playing-games) [Github](https://github.com/AndyYue1893/pwc) 273 | 274 | ### 3. Course and Code 275 | - 腾讯_周沫凡_强化学习、教程、代码 [bilibili](https://www.bilibili.com/video/av16921335?from=search&seid=7037144790835305588) [个人主页](https://morvanzhou.github.io/) [Github](https://github.com/AndyYue1893/Reinforcement-learning-with-tensorflow) 276 | - DeepMind_David Silver_UCL深度强化学习课程(2015)、PPT、笔记及代码 [bilibili](https://www.bilibili.com/video/av45357759?from=search&seid=7037144790835305588) [zhihu](https://zhuanlan.zhihu.com/p/37690204) 277 | - 台大_李宏毅_深度强化学习(国语)课程(2018)、PPT、笔记 [bilibili](https://www.bilibili.com/video/av24724071?from=search&seid=7037144790835305588) [PPT](http://speech.ee.ntu.edu.tw/~tlkagk/courses_MLDS18.html) [note](https://blog.csdn.net/cindy_1102/article/details/87904928) 278 | - Berkeley_Sergey Levine_CS285(294)深度强化学习(2019)、PPT、代码 [bilibili](https://www.bilibili.com/video/av69455099?from=search&seid=7037144790835305588) [PPT](http://rail.eecs.berkeley.edu/deeprlcourse/) [Github](https://github.com/berkeleydeeprlcourse/homework) 279 | 280 | --- 281 | 282 | 283 | ## C/C++ 284 | - C/C++面试基础知识总结 [Github](https://github.com/huihut/interview) 285 | - 常见C++笔试面试题整理 [zhihu](https://zhuanlan.zhihu.com/p/69999591) 286 | - C/C++问题总结 [Github](https://github.com/linw7/Skill-Tree/blob/master/%E7%BC%96%E7%A8%8B%E8%AF%AD%E8%A8%80C++.md) 287 | - Leetcode 题解代码仓(C++) [Github](https://github.com/liuyubobobo/Play-Leetcode) 288 | - LeetCode, HackRank, 剑指offer, classic algorithm implementation (C++) [Github](https://github.com/knightsj/awesome-algorithm-question-solution) 289 | - Data Structure and Algorithm notes数据结构与算法/leetcode/lintcode题解 [Github](https://github.com/billryan/algorithm-exercise) 290 | - learnOpencv [Github](https://github.com/spmallick/learnopencv) 291 | - Solutions to Introduction to Algorithms Third Edition [Github](https://github.com/walkccc/CLRS/) [Blog](https://walkccc.github.io/CLRS/) 292 | - LeetCode动画 [Github](https://github.com/MisterBooo/LeetCodeAnimation) 293 | - leetcode题解，记录自己的leetcode解题之路 [Github](https://github.com/azl397985856/leetcode) 294 | - 剑指offer第二版 [BaiduYun](https://pan.baidu.com/s/1wU-8q3Mqvr3x6Et8t77Chg) 295 | - <算法导论>的C++实现代码 [Github](https://github.com/huaxz1986/cplusplus-_Implementation_Of_Introduction_to_Algorithms) 296 | - 数据结构和算法必知必会的50个代码实现 [Github](https://github.com/wangzheng0822/algo) 297 | - Play Leetcode with different Programming language [Github](https://github.com/luliyucoordinate/Leetcode) 298 | - leetcode [Github](https://github.com/azl397985856/leetcode) 299 | - algorithm-visualizer [Github](https://github.com/algorithm-visualizer/algorithm-visualizer) 300 | - 基于OpenCV4.0 C++/Python SDK的案例代码演示程序与效果图像 [Github](https://github.com/gloomyfish1998/opencv_tutorial) 301 | - LeetCode solutions in C++ 11 and Python3 [Github](https://github.com/pezy/LeetCode) 302 | 303 | --- 304 | 305 | ## Python 306 | - cracking the coding interview [Github](https://github.com/keyejia/Cracking-the-coding-interview-in-Python) 307 | - Python 开源项目大集合，跨 15 个领域，181 个项目 [Github](https://github.com/mahmoud/awesome-python-applications) 308 | - 关于Python的面试题1 [Github](https://github.com/taizilongxu/interview_python) 309 | - 关于Python的面试题2 [Github](https://github.com/kenwoodjw/python_interview_question) 310 | - LeetCode, HackRank, 剑指offer, classic algorithm implementation (Python) [Github](https://github.com/apachecn/awesome-algorithm) 311 | - 剑指offer（python版）/ 算法图解 / python基础 / 数据结构 [Github](https://github.com/weixianglin/oh-my-python) 312 | - 算法面试题python [Github](https://github.com/leeguandong/Interview-code-practice-python) 313 | - All Algorithms implemented in Python [Github](https://github.com/TheAlgorithms/Python) 314 | - Improve your Python by fixing errors [Github](https://github.com/qxf2/wtfiswronghere) 315 | - wtfpython的中文翻译 [Github](https://github.com/leisurelicht/wtfpython-cn) 316 | - python中文库-python人工智能大数据自动化接口测试开发。书籍下载及python库汇总 [Github](https://github.com/china-testing/python-api-tesing) 317 | - Python面试都在这里了【315+道题】 [Blog](https://www.cnblogs.com/wupeiqi/p/9078770.html) 318 | - The Beauty of Python Programming [Github](https://github.com/ethan-funny/explore-python) 319 | - Python - 100天从新手到大师 [Github](https://github.com/jackfrued/Python-100-Days) 320 | - 在 Windows 上使用 Python 进行开发 [Blog](https://docs.microsoft.com/zh-cn/windows/python/) 321 | - A curated list of awesome Python frameworks, libraries, software and resources [Github](https://github.com/vinta/awesome-python) 322 | - c9-python-getting-started [Github](https://github.com/microsoft/c9-python-getting-started) 323 | - 编程超能力入门班 [Blog](www.enginego.org) 324 | 325 | --- 326 | 327 | 328 | ## Pytorch 329 | - pytorch [Github](https://github.com/pytorch/pytorch) [Website](https://pytorch.org/) 330 | - Offical pytorch examples [Github](https://github.com/pytorch/examples) 331 | - Offical pytorch tutorials [Github](https://github.com/pytorch/tutorials) 332 | - stanford-cs-230-deep-learning [Github](https://github.com/afshinea/stanford-cs-230-deep-learning) 333 | - practicalAI [Github](https://github.com/GokuMohandas/practicalAI) 334 | - PyTorch中文手册 [Github](https://github.com/zergtant/pytorch-handbook) 335 | - <深度学习框架PyTorch：入门与实践>的对应代码 [Github](https://github.com/chenyuntc/pytorch-book) 336 | - code-of-learn-deep-learning-with-pytorch [Github](https://github.com/L1aoXingyu/code-of-learn-deep-learning-with-pytorch) 337 | - Awesome-pytorch-list [Github](https://github.com/bharathgs/Awesome-pytorch-list) 338 | - 中配套代码 [Github](https://github.com/tensor-yu/PyTorch_Tutorial) 339 | - An unofficial styleguide and best practices summary for PyTorch [Github](https://github.com/IgorSusmelj/pytorch-styleguide) 340 | - fast.ai Computational Linear Algebra course [Github](https://github.com/fastai/numerical-linear-algebra) 341 | - Awesome-PyTorch-Chinese [Github](https://github.com/INTERMT/Awesome-PyTorch-Chinese) 342 | - Build-an-AI-Startup-with-PyTorch [Github](https://github.com/llSourcell/Build-an-AI-Startup-with-PyTorch) 343 | - First steps towards Deep Learning with pyTorch [Github](https://github.com/vaibhawvipul/First-steps-towards-Deep-Learning) 344 | 345 | --- 346 | 347 | 348 | ## Tensorflow 349 | - TensorFlow 2.0 深度学习开源书 [Github](https://github.com/dragen1860/Deep-Learning-with-TensorFlow-book) 350 | - TensorFlow-From-Zero-To-One [Github](https://github.com/amusi/TensorFlow-From-Zero-To-One) 351 | - tensorflow2中文教程 [Github](https://github.com/czy36mengfei/tensorflow2_tutorials_chinese) 352 | - Tensorflow2教程 [Github](https://zhuanlan.zhihu.com/c_1091021863043624960) 353 | - Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2 [Github](https://github.com/ageron/handson-ml2) 354 | - TensorFlow 中文资源全集 [Gitee](https://gitee.com/fendouai/Awesome-TensorFlow-Chinese) 355 | - Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course [Github](https://github.com/ageron/tf2_course) 356 | 357 | --- 358 | 359 | 360 | ## Competition 361 | - [kaggle数据科学竞赛](https://www.kaggle.com/competitions) 362 | - [阿里云天池比赛](https://tianchi.aliyun.com/competition/gameList/activeList) 363 | - [AI Challenger](https://challenger.ai/?lan=zh) 364 | - [和鲸HeyWhale/科赛AI竞赛平台](https://www.kesci.com/home/competition) 365 | - [FlyAI竞赛平台](https://www.flyai.com/) 366 | - [BaiduAI竞赛](https://aistudio.baidu.com/aistudio/#/competition) 367 | - [DC竞赛](http://www.dcjingsai.com/static_page/cmpList.html) 368 | - [DataFountain竞赛](https://www.datafountain.cn/competitions) 369 | - [日本SIGNATE竞赛](https://signate.jp/competitions) 370 | - [Awesome-AI-competitions](https://github.com/HuangCongQing/AI_competitions) 371 | - [Driven Data](https://www.drivendata.org/competitions/) 372 | - [CrowdANALYTIX](https://www.crowdanalytix.com/community) 373 | - [CodaLab](https://competitions.codalab.org/) 374 | - [Analytics Vidhya](https://datahack.analyticsvidhya.com/?utm_source=main-logo) 375 | - [crowdAI](https://www.crowdai.org/challenges) 376 | - [Data Science Challenges](https://www.datasciencechallenge.org/) 377 | 378 | --- 379 | 380 | ## Others 381 | - Awesome Resume for Chinese [Github](https://github.com/dyweb/awesome-resume-for-chinese) 382 | - 个人简历模板 [Github](https://github.com/ikym/resume) 383 | - 程序员简历模板系列 [Github](https://github.com/geekcompany/ResumeSample) 384 | - 如何写一份专业的技术简历 [Website](https://mp.weixin.qq.com/s?__biz=MzA5NDk4NDcwMw==&mid=2651388719&idx=1&sn=84ec4d342f85199b7f4dd5bdaa535949&chksm=8bba1bbfbccd92a9425c7dd0efdf4924c0308bb62ee6808f202c7a8f52fd6b78e43ed954bbb9&scene=0&xtrack=1&key=ff1b1d089c15295c18c4772c5513870b3f444ddfc7eedefb34d50858e7be4c2d678cac2b24aa0356f577aa7c34a5bacdfdcac62bace0a0b7ec262694292724fd25f4c1ec3d115ad041ea0fc899723239&ascene=14&uin=MTM2NDUyMTkxOQ%3D%3D&devicetype=Windows+10&version=62070158&lang=zh_CN&exportkey=AzjSleucIgNxHjJEKgZIQkc%3D&pass_ticket=isK%2FwATeORDKA144xaM2%2FZkXRQIChncFMP25btSedNMCRsZBUEgl7YxoVEFxq8eQ) 385 | - awesome-interview-questions [Github](https://github.com/MaximAbramchuck/awesome-interview-questions) 386 | - Startups about artificial intelligence. (DM, ML, NLP, CV...) [Github](https://github.com/lipiji/AIStartups) 387 | - Awesome Programming Books [Github](https://github.com/majikarp/awesome-programming-books#id-section2) 388 | - 清华大学计算机系课程攻略 [Github](https://github.com/PKUanonym/REKCARC-TSC-UHT) 389 | - 北京大学课程资料整理 [Github](https://github.com/lib-pku/libpku) 390 | - 中国科学技术大学课程资源 [Github](https://github.com/USTC-Resource/USTC-Course) 391 | - 上海交通大学课程资料分享 [Github](https://github.com/CoolPhilChen/SJTU-Courses/) 392 | - 浙江大学课程攻略共享计划 [Github](https://github.com/QSCTech/zju-icicles) 393 | 394 | 395 | 396 | 397 | --------------------------------------------------------------------------------