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编辑:数据派THU
Github传送门:
https://github.com/lcylmhlcy/Awesome-algorithm-interview
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算法工程师
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Github

  • 算法/深度学习/NLP面试笔记 Github
    • https://github.com/imhuay/Algorithm_Interview_Notes-Chinese
  • 算法工程师面试 Github
    • https://github.com/PPshrimpGo/AIinterview

  • 2019届秋招面经集合 Github
    • https://github.com/zslomo/2019-Autumn-recruitment-experience

  • 技术面试必备基础知识 Github
    • https://github.com/CyC2018/CS-Notes
  • AI算法岗求职攻略 Github (amusi)
    • https://github.com/amusi/AI-Job-Notes
  • 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-
  • (面试算法练级攻略)-(LeetCode题解)-(剑指offer题解)」Github
    • https://github.com/guokaide/algorithm
  • MVision-awesome Github
    • https://github.com/Ewenwan/MVision
  • 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
  • Daily Interview Github
    • https://github.com/datawhalechina/Daily-interview
  • 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
牛客网
  • 旷视19届春招-算法研究员-凉经 nowcoder
    • https://www.nowcoder.com/discuss/167336
  • 腾讯算法实习面试总结 nowcoder
    • https://www.nowcoder.com/discuss/163996
  • 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
  • 普通的算法/机器学习面经 nowcoder
    • https://www.nowcoder.com/discuss/61907
  • 20届-视觉算法-暑期实习 nowcoder
    • https://www.nowcoder.com/discuss/173292
  • 字节跳动实习算法岗面经 nowcoder
    • https://www.nowcoder.com/discuss/174565
  • 阿里腾讯虎牙机器学习算法面经 nowcoder
    • https://www.nowcoder.com/discuss/175759
  • 字节跳动图形图像算法实习面经 nowcoder
    • https://www.nowcoder.com/discuss/178153
  • 拼多多算法实习生面经 nowcoder
    • https://www.nowcoder.com/discuss/177911
  • 算法岗面经传送门 nowcoder
    • https://www.nowcoder.com/discuss/180976
  • 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
  • cv岗面经 nowcoder
    • https://www.nowcoder.com/discuss/159266
  • 小菜鸡的算法实习面经 nowcoder
    • https://www.nowcoder.com/discuss/181770
  • 机器学习/算法校招面试考点汇总 nowcoder
    • https://www.nowcoder.com/discuss/165930
  • 计算机视觉暑期实习面经 nowcoder
    • https://www.nowcoder.com/discuss/186000
  • 算法岗面经(阿里云,1,2,3,交叉,hr面) nowcoder
    • https://www.nowcoder.com/discuss/172079
  • 春招实习面经(cv算法岗) nowcoder
    • https://www.nowcoder.com/discuss/183555
  • 双非本硕算法陪跑面经 nowcoder
    • https://www.nowcoder.com/discuss/186247
  • 2018春招科大讯飞,华为,神策数据,今日头条面经 nowcoder
    • https://www.nowcoder.com/discuss/75136?type=2&order=3&pos=254&page=1
  • 2020届渣硕春招实习总结-算法岗(计算机视觉) nowcoder
    • https://www.nowcoder.com/discuss/186113
  • 爱奇艺深度学习算法实习生面经 nowcoder
    • https://www.nowcoder.com/discuss/185614
  • 阿里,旷视,亚马逊,谷歌面经 nowcoder
    • https://www.nowcoder.com/discuss/172693
  • 算法菜鸟的春招之路 nowcoder
    • https://www.nowcoder.com/discuss/188295
  • 机器学习算法面经(腾讯阿里网易) nowcoder
    • https://www.nowcoder.com/discuss/75166?type=2&order=3&pos=250&page=1
  • 实习算法岗血泪面经,商汤,旷世,阿里,字节跳动 nowcoder
    • https://www.nowcoder.com/discuss/192689?type=2
  • 机器学习/数据挖掘岗2019秋招总结 nowcoder
    • https://www.nowcoder.com/discuss/138721
  • 算法面经(阿里、腾讯、美团等) nowcoder
    • https://www.nowcoder.com/discuss/77924?type=2&order=3&pos=195&page=1
  • 春招秋招算法机器学习岗面经(阿里、腾讯、美团、携程) nowcoder
    • https://www.nowcoder.com/discuss/106725
  • 春招(附面经) nowcoder
    • https://www.nowcoder.com/discuss/79729
  • 计算机视觉算法岗面经 nowcoder
    • https://www.nowcoder.com/discuss/128148
  • 机器学习算法面经---2018秋招 nowcoder
    • https://www.nowcoder.com/discuss/32008
  • 阿里&腾讯春招算法面经 nowcoder
    • https://www.nowcoder.com/discuss/198290?type=2&order=3&pos=7&page=1
  • 阿里暑期实习六面面经 nowcoder
    • https://www.nowcoder.com/discuss/180007
  • 计算机视觉算法岗面经 nowcoder
    • https://www.nowcoder.com/discuss/128148
  • 阿里 达摩院 cv 算法 面经 nowcoder
    • https://www.nowcoder.com/discuss/216797
  • 算法工程师面经 寒拼蘑腾作网网3 附答案 nowcoder
    • https://www.nowcoder.com/discuss/231656
  • 搜狗算法面经 nowcoder
    • https://www.nowcoder.com/discuss/231973
  • 商汤20校招CV算法研究员面经(三面+HR面) nowcoder
    • https://www.nowcoder.com/discuss/209857
  • 作业帮/寒武纪/商汤/科大讯飞面经 nowcoder
    • https://www.nowcoder.com/discuss/218906
  • 面经 | 腾讯/百度/字节跳动/拼多多/华为/美团/寒武纪/虎牙等 nowcoder
    • https://www.nowcoder.com/discuss/241988
  • 算法秋招上岸了,大家加油,我先撤了(附所有面经) nowcoder
    • https://www.nowcoder.com/discuss/244979

知乎
  • 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
  • 做计算机视觉的你,如何拿到大厂的Offer的?可否分享下?zhihu
    • https://www.zhihu.com/question/272045026/answer/366665187
  • 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
  • 2019秋招算法面经 zhihu
    • https://zhuanlan.zhihu.com/p/42936891
  • CVTE视觉计算岗实习面经 zhihu
    • https://zhuanlan.zhihu.com/p/59223324
  • 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
  • 计算机视觉(cv)方向今年招聘情况怎么样?是否已经人才过剩? zhihu
    • https://www.zhihu.com/question/293700785
个人博客
  • AI算法工程师手册 Blog
    • http://www.huaxiaozhuan.com/
  • 小米面试总结 Blog
    • https://wx.qnmlgb.tech/articles/5c55c999ce56ab804b1526cd/
  • 百度/商汤AI面试 CSDN
    • https://blog.csdn.net/emma1222/article/details/86551435
  • 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
  • CV计算机论文速览 CSDN
    • https://me.csdn.net/u014636245
微信公众号
  • 阿里巴巴计算机视觉算法实习生视频面试 website
    • https://bit.ly/2n6xJNw

  • 面试经验AI算法工程师(面试官角度) website
    • https://bit.ly/2nLRaLX

  • 从零基础到BAT算法岗SP——秋招准备攻略 website
    • https://bit.ly/2luBZpw

  • 蚂蚁金服/旷视/虹软/腾讯优图暑期实习offer面经 website
    • https://bit.ly/2nGEeXy

  • 我在美团的这两年(附校招笔试/面试/面经分享) website
    • https://bit.ly/2lyxQ3Y
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  • 1000 面试题,BAT 机器学习面试刷题宝典!website
    • https://bit.ly/2nKXnHZ

  • 如何拿到自己满意的offer?website
    • https://bit.ly/2nGFnOQ

  • 机器学习与深度学习常见面试题(上) website
    • https://bit.ly/2nDAG8q

  • 机器学习与深度学习常见面试题(下) website
    • https://bit.ly/2mfFLU5

  • 完备的 AI 学习路线,最详细的资源整理!website
    • https://bit.ly/2nE3m15

  • 蚂蚁金服面经(已拿 Offer) website
    • https://bit.ly/2m4Fzaq

  • 30家企业海投,10余家offer,我的漫漫秋招之旅 website
    • https://bit.ly/2lyjwsb

  • BAT 三连挂是什么体验?硕士小姐姐讲述心酸血泪史!website
    • https://bit.ly/2nJmWcl

  • 数据科学&机器学习基础面试题 website
    • https://bit.ly/2lBuRYH

  • 计算机视觉、算法岗实习面经(阿里/格灵深瞳/南京地平线机器人) website
    • https://bit.ly/2nMscvZ

  • 面经 | 挂两次腾讯面试的春招教训 website
    • https://bit.ly/2n6MzDG

  • Face++公司 - 两轮技术面试面经 website
    • https://bit.ly/2mdCHb9

  • 秋招面经 | 旷视科技算法岗秋招面试经验分享 website
    • https://bit.ly/2lCy8qE

  • 面经+经验分享|2019秋招算法岗复盘 website
    • https://bit.ly/2mfZi6P

  • 专科生阿里大数据一面面经(已过) website
    • https://bit.ly/2lDzbqm

  • 2019秋招算法岗复盘 website
    • https://bit.ly/2nGprMt

  • 我面试了10家算法公司,这是我能记住的所有问题 website
    • https://bit.ly/2lyC2AJ

  • 计算机视觉算法工程师(旷视、商汤、智云、海康)面试总结 website
    • https://bit.ly/2nbjZAW

  • 秋招面经 | 滴滴20校招CV算法岗面试经验分享(三面) website
    • https://bit.ly/2ncyt3u

  • 八家国企大数据面经(干货,详细答案) website
    • https://bit.ly/2ndSxT9

其他
  • 廖雪峰AI面试资料 BaiduYun ps:uzj9
    • https://pan.baidu.com/s/10NL2yJxsBFjq8PP-wdBfuw
    • ps:uzj9
  • Solutions to Introduction to Algorithms Github
    • https://github.com/gzc/CLRS
  • CV 领域论文常见单词 zhihu
    • https://zhuanlan.zhihu.com/p/60049093
  • CV领域Paper论文常见单词 zhihu
    • https://zhuanlan.zhihu.com/p/58860096
  • Everything you need to know to get the job Github
    • https://github.com/kdn251/interviews
  • Everything you need to prepare for your technical interview Github
    • https://github.com/andreis/interview
  • Materials to help you rock your next coding interview Github
    • https://github.com/yangshun/tech-interview-handbook
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机器学习
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面试问题
  • 机器学习面试算法梳理 Blog
    • https://www.cnblogs.com/tornadomeet/p/3395593.html
  • 面试官如何判断面试者的机器学习水平 zhihu
    • https://www.zhihu.com/question/62482926
  • machine-learning-interview-questions Github
    • https://github.com/Sroy20/machine-learning-interview-questions
  • 机器学习与深度学习面试问题总结 Blog
    • https://bit.ly/2mgUSfY

  • 机器学习面试复习资源 Github
    • https://github.com/wangyuGithub01/Machine_Learning_Resources
资料
  • Your new Mentor for Data Science E-Learning Github
    • https://github.com/clone95/Virgilio
  • 王斌老师翻译的<机器学习实战>书python代码实现 Github
    • https://github.com/wzy6642/Machine-Learning-in-Action-Python3
  • PRML(python) Github
    • https://github.com/ctgk/PRML
  • 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
  • <统计学习方法>第二版的代码实现 Github
    • https://github.com/fengdu78/lihang-code
  • <机器学习>(西瓜书)公式推导解析 Github
    • https://github.com/datawhalechina/pumpkin-book
  • <数据科学实战>书代码 Github
    • https://github.com/oreillymedia/doing_data_science
  • 机器学习实战(Python3) Github
    • https://github.com/Jack-Cherish/Machine-Learning
  • 吴恩达讲授的机器学习 Coursera 163
    • https://www.coursera.org/learn/machine-learning
  • Solutions to Introduction to Algorithms Third Edition Github
    • https://github.com/walkccc/CLRS
  • Data-Science--Cheat-Sheet Github
    • https://github.com/abhat222/Data-Science--Cheat-Sheet
  • Data Science Crash Course Github
    • https://maria-antoniak.github.io/2018/11/19/data-science-crash-course.html
  • List of Data Science Cheatsheets to rule the world Github
    • https://github.com/FavioVazquez/ds-cheatsheets
  • Your new Mentor for Data Science E-Learning. Github
    • https://github.com/virgili0/Virgilio
  • Python3 入门机器学习 Github
    • https://github.com/liuyubobobo/Play-with-Machine-Learning-Algorithms
  • DrWhy is the collection of tools for Explainable AI (XAI) Github
    • https://github.com/ModelOriented/DrWhy
  • Fit interpretable models. Explain blackbox machine learning. Github
    • https://github.com/jwasham/coding-interview-university
  • 李宏毅《机器学习》笔记 Github
    • https://github.com/datawhalechina/leeml-notes
  • 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
代码实战

  • 机器学习算法python实现 Github
    • https://github.com/lawlite19/MachineLearning_Python
  • 100-Days-Of-ML-Code中文版 Github
    • https://github.com/MLEveryday/100-Days-Of-ML-Code
  • Homemade Machine Learning Github
    • https://github.com/trekhleb/homemade-machine-learning
  • Python codes for common Machine Learning Algorithms Github
    • https://github.com/susanli2016/Machine-Learning-with-Python
  • Machine-Learning-Study-Path-March-2019 Github
    • https://github.com/clone95/Machine-Learning-Study-Path-March-2019
  • The best resources in Machine Learning & AI Github Website
    • https://github.com/RemoteML/bestofml
    • https://bestofml.com/
  • AiLearning- ML、深度学习 Github
    • https://github.com/apachecn/AiLearning
  • A Machine Learning Course with Python Github
    • https://github.com/machinelearningmindset/machine-learning-course
  • Machine learning, in numpy Github
    • https://github.com/ddbourgin/numpy-ml
  • A complete computer science study plan to become a software engineer. Github
    • https://github.com/ddbourgin/numpy-ml

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深度学习
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面试
  • 深度学习面试问题 Github
    • https://github.com/elviswf/DeepLearningBookQA_cn
  • 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
  • Deep Learning Interview 深度学习面试题目汇总 Github
    • https://github.com/ShanghaiTechAIClub/DLInterview
  • 深度学习面试要点总结(面试题) zhihu
    • https://zhuanlan.zhihu.com/p/62935978
  • 自己整理的一点和深度学习相关的面试考点
    • https://zhuanlan.zhihu.com/p/48374690
资料
  • 深度神经网络实战技巧 Blog
    • https://bit.ly/2nJvQXj

  • 深度学习从入门到进阶的12个经典问题及解答 Blog
    • https://bit.ly/2lBD0ML

  • 计算机视觉知识点总结 zhihu
    • https://zhuanlan.zhihu.com/p/58776542
  • 图解人工智能 Github
    • https://okai.brown.edu/zh/index.html
  • awesome-deep-learning Github
    • https://github.com/ChristosChristofidis/awesome-deep-learning
  • 深度学习500问 Github
    • https://github.com/scutan90/DeepLearning-500-questions
  • 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
  • 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 https://github.com/dsgiitr/d2l-pytorch
  • <深度学习理论与实战:提高篇> Github
    • http://fancyerii.github.io/2019/03/14/dl-book/
  • Awesome_Computer_Vision Github
    • https://github.com/ahong007007/Awesome_Computer_Vision
  • Deep-Learning-Papers-Reading-Roadmap Github
    • https://github.com/floodsung/Deep-Learning-Papers-Reading-Roadmap
  • 神经网络讲解视频
    • YouTube https://youtu.be/aircAruvnKk?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
    • bilibilihttp://space.bilibili.com/88461692/#/
  • 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/
  • 花书 Deep Learning 中文版 Github
    • https://github.com/exacity/deeplearningbook-chinese
  • Open AI Blog website
    • https://blog.openai.com/
  • Distill Blog website
    • https://distill.pub/
  • BAIR 博客 website
    • http://bair.berkeley.edu/blog/
  • DeepMind 博客 website
    • https://deepmind.com/blog/?category=research
  • Andrej Karpathy的博客 website
    • http://karpathy.github.io/
  • Christopher Olah的博客 website
    • http://colah.github.io/
  • WildML Blog website
    • http://www.wildml.com/
  • Ruder的博客 website
    • http://ruder.io/
  • FAIR博客 website
    • https://research.fb.com/blog/
  • inFERENCe Blog website
    • http://www.inference.vc/
  • Andrew Trask的博客 website
    • http://iamtrask.github.io/
  • Graduate Descent Blog website
    • http://timvieira.github.io/blog/
  • Adit Deshpande的博客 website
    • https://adeshpande3.github.io/
  • ML/DL学习笔记(基础+论文) Github
    • https://github.com/lartpang/Machine-Deep-Learning
  • 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
  • five-days deep learning
    • website https://mlelarge.github.io/dataflowr-web/cea_edf_inria.html
    • Github https://github.com/mlelarge/dataflowr
  • Learn_Computer_Vision Github
    • https://github.com/llSourcell/Learn_Computer_Vision
  • Explaining the Math of how neural networks learn Github
    • https://github.com/omar-florez/scratch_mlp
  • (微软) AI-神经网络基本原理简明教程 Github
    • https://github.com/microsoft/ai-edu/tree/master/
  • 深度学习手册 BaiduYun pw:dy6h
    • https://pan.baidu.com/s/1ew3aVZizVkPVKUFx2AtDjw
    • pw:dy6h
  • An educational resource to help anyone learn deep reinforcement learning Github
    • https://github.com/openai/spinningup
  • Technical Notes On Using Data Science & Artificial Intelligence website
    • https://chrisalbon.com/
代码实战Pytorch
  • pytorch
    • Github https://github.com/pytorch/pytorch
    • Website https://pytorch.org/
  • Offical pytorch examples Github
    • https://github.com/pytorch/examples
  • Offical pytorch tutorials Github
    • https://github.com/pytorch/tutorials
  • stanford-cs-230-deep-learning Github
    • https://github.com/afshinea/stanford-cs-230-deep-learning
  • practicalAI Github
    • https://github.com/GokuMohandas/practicalAI
  • PyTorch中文手册 Github
    • https://github.com/zergtant/pytorch-handbook
  • <深度学习框架PyTorch:入门与实践>的对应代码 Github
    • https://github.com/chenyuntc/pytorch-book
  • code-of-learn-deep-learning-with-pytorch Github
    • https://github.com/L1aoXingyu/code-of-learn-deep-learning-with-pytorch
  • Awesome-pytorch-list Github
    • https://github.com/bharathgs/Awesome-pytorch-list
  • 中配套代码 Github
    • https://github.com/tensor-yu/PyTorch_Tutorial
  • An unofficial styleguide and best practices summary for PyTorch Github
    • https://github.com/IgorSusmelj/pytorch-styleguide
  • fast.ai Computational Linear Algebra course Github
    • https://github.com/fastai/numerical-linear-algebra
  • Awesome-PyTorch-Chinese Github
    • https://github.com/INTERMT/Awesome-PyTorch-Chinese
  • Build-an-AI-Startup-with-PyTorch Github
    • https://github.com/llSourcell/Build-an-AI-Startup-with-PyTorch
代码实战TensorFlow
  • TensorFlow-From-Zero-To-One Github
    • https://github.com/amusi/TensorFlow-From-Zero-To-One
  • tensorflow2中文教程 Github
    • https://github.com/czy36mengfei/tensorflow2_tutorials_chinese
  • Tensorflow2教程 Github
    • https://zhuanlan.zhihu.com/c_1091021863043624960
  • Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2 Github
    • https://github.com/ageron/handson-ml2
  • TensorFlow 中文资源全集 Gitee
    • https://gitee.com/fendouai/Awesome-TensorFlow-Chinese
  • Notebooks for my "Deep Learning with TensorFlow 2 and Keras" course Github
    • https://github.com/ageron/tf2_course
网课
  • 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
  • 统计机器学习 网易云课堂
    • https://study.163.com/course/courseMain.htm?courseId=1692004
  • 机器学习导论 网易云课堂
    • https://study.163.com/course/courseMain.htm?courseId=1694003
  • 吴恩达 深度学习工程师 网易云课堂
    • https://mooc.study.163.com/smartSpec/detail/1001319001.htm
  • 计算机视觉基础入门课程(从算法到实战应用) AI研习社
    • http://www.mooc.ai/course/353
  • 卡耐基梅隆大学 2018 秋季《深度学习导论》 AI研习社
    • http://www.mooc.ai/course/562
  • CS224n 斯坦福深度自然语言处理课 AI研习社
    • http://www.mooc.ai/course/494
  • 2018 MIT 6.S094 麻省理工深度学习和自动驾驶课程 AI研习社
    • http://www.mooc.ai/course/483
  • Deep Learning: Advanced Computer Vision udemy
    • https://www.udemy.com/advanced-computer-vision/
  • Computer Vision Certification by State University of New York coursera
    • https://www.coursera.org/specializations/computervision
  • Convolutional Neural Networks coursera
    • https://www.coursera.org/learn/convolutional-neural-networks
  • Deep Learning and Computer Vision A-Z: OpenCV, SSD & GANs udemy
    • https://www.udemy.com/course/computer-vision-a-z/
  • 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/
  • CS231n
    • http://cs231n.stanford.edu/
  • CS224n
    • http://web.stanford.edu/class/cs224n/
  • 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
  • MIT公开课线性代数'Linear Algebra' website
    • https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/
  • 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 website
    • https://course.fast.ai/
    • https://www.bilibili.com/video/av41718196/
  • 斯坦福机器学习课程'Machine Learning(Coursera)' coursera
    • https://www.coursera.org/learn/machine-learning
  • 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
  • DeepMind强化学习导论课程'Introduction to Reinforcement Learning'
    • bilibilihttps://www.bilibili.com/video/av24060851/
    • youtube https://www.youtube.com/playlist?list=PLqYmG7hTraZDM-OYHWgPebj2MfCFzFObQ
  • 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'
    • Githubhttps://github.com/full-stack-deep-learning/fsdl-text-recognizer-project
    • bilibilihttps://www.bilibili.com/video/av49643298
    • websitehttps://fullstackdeeplearning.com/march2019
  • 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
  • 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/
  • 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/
  • 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
  • deeplearning.ai上线的TensorFlow实践课程'TensorFlow in Practice' website
    • https://www.deeplearning.ai/tensorflow-in-practice/
  • 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
  • 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
  • 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/
  • 台大林轩田老师<机器学习基石>课程 bilibili

    • https://www.bilibili.com/video/av12463015/
  • 台大林轩田老师课程<机器学习技法>课程 bilibili

    • https://www.bilibili.com/video/av12469267/
  • 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

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C/C++
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  • C/C++面试基础知识总结 Github
    • https://github.com/huihut/interview
  • 常见C++笔试面试题整理 zhihu
    • https://zhuanlan.zhihu.com/p/69999591
  • 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
  • Leetcode 题解代码仓(C++) Github
    • https://github.com/liuyubobobo/Play-Leetcode
  • LeetCode, HackRank, 剑指offer, classic algorithm implementation (C++) Github
    • https://github.com/knightsj/awesome-algorithm-question-solution
  • Data Structure and Algorithm notes数据结构与算法/leetcode/lintcode题解 Github
    • https://github.com/billryan/algorithm-exercise
  • learnOpencv Github
    • https://github.com/spmallick/learnopencv
  • Solutions to Introduction to Algorithms Third Edition
    • Github https://github.com/walkccc/CLRS/
    • Blog https://walkccc.github.io/CLRS/
  • LeetCode动画 Github
    • https://github.com/MisterBooo/LeetCodeAnimation
  • leetcode题解,记录自己的leetcode解题之路 Github
    • https://github.com/azl397985856/leetcode
  • 剑指offer第二版 BaiduYun
    • https://pan.baidu.com/s/1wU-8q3Mqvr3x6Et8t77Chg
  • <算法导论>的C++实现代码 Github
    • https://github.com/huaxz1986/cplusplus-_Implementation_Of_Introduction_to_Algorithms
  • 数据结构和算法必知必会的50个代码实现 Github
    • https://github.com/wangzheng0822/algo
  • Play Leetcode with different Programming language Github
    • https://github.com/luliyucoordinate/Leetcode
  • leetcode Github
    • https://github.com/azl397985856/leetcode
  • algorithm-visualizer Github
    • https://github.com/algorithm-visualizer/algorithm-visualizer
  • 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
  • LeetCode solutions in C++ 11 and Python3 Github
    • https://github.com/pezy/LeetCode

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Python
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  • 关于Python的面试题1 Github
    • https://github.com/taizilongxu/interview_python
  • 关于Python的面试题2 Github
    • https://github.com/kenwoodjw/python_interview_question
  • LeetCode, HackRank, 剑指offer, classic algorithm implementation (Python) Github
    • https://github.com/apachecn/awesome-algorithm
  • 剑指offer(python版)/ 算法图解 / python基础 / 数据结构 Github
    • https://github.com/weixianglin/oh-my-python
  • 算法面试题python Github
    • https://github.com/leeguandong/Interview-code-practice-python
  • All Algorithms implemented in Python Github
    • https://github.com/TheAlgorithms/Python
  • Improve your Python by fixing errors Github
    • https://github.com/qxf2/wtfiswronghere
  • wtfpython的中文翻译 Github
    • https://github.com/leisurelicht/wtfpython-cn
  • 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
  • Python面试都在这里了【315+道题】 Blog
    • https://github.com/ethan-funny/explore-python
  • The Beauty of Python Programming Github
    • https://github.com/jackfrued/Python-100-Days
  • Python - 100天从新手到大师 Github
    • https://github.com/jackfrued/Python-100-Days
  • 在 Windows 上使用 Python 进行开发 Blog
    • https://github.com/vinta/awesome-python
  • A curated list of awesome Python frameworks, libraries, software and resources Github
    • https://github.com/vinta/awesome-python

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竞赛/比赛
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  • kaggle数据科学竞赛
    • https://tianchi.aliyun.com/competition/gameList/activeList
  • 阿里云天池比赛
    • https://challenger.ai/?lan=zh
  • AI Challenger
    • https://challenger.ai/?lan=zh
  • 和鲸HeyWhale/科赛AI竞赛平台
    • https://www.kesci.com/home/competition
  • FlyAI竞赛平台
    • https://aistudio.baidu.com/aistudio/#/competition
  • BaiduAI竞赛
    • http://www.dcjingsai.com/static_page/cmpList.html
  • DC竞赛
    • http://www.dcjingsai.com/static_page/cmpList.html
  • DataFountain竞赛
    • https://signate.jp/competitions
  • 日本SIGNATE竞赛
    • https://signate.jp/competitions
  • Awesome-AI-competitions
    • https://github.com/HuangCongQing/AI_competitions
  • Driven Data
    • https://www.drivendata.org/competitions/
  • CrowdANALYTIX
    • https://www.innocentive.com/our-solvers/
  • InnoCentive
    • https://www.innocentive.com/our-solvers/
  • TunedIT Challenges
    • https://competitions.codalab.org/
  • CodaLab
    • https://datahack.analyticsvidhya.com/?utm_source=main-logo
  • Analytics Vidhya
    • https://www.crowdai.org/challenges
  • crowdAI
    • https://www.datasciencechallenge.org/
  • Data Science Challenges
    • https://www.datasciencechallenge.org/

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简历模板
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  • Awesome Resume for Chinese Github
    • https://github.com/amusi/AI-Job-Resume
  • 【推荐收藏|推荐收藏 | 算法工程师常见面试问题及相关资料汇总】AI算法岗简历模板 Github
    • https://github.com/amusi/AI-Job-Resume
  • 个人简历模板 Github
    • https://github.com/ikym/resume

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其他
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  • 博士生在没有导师指导的情况下,该如何自己选题发 CVPR zhihu
    • https://www.zhihu.com/question/64566768
  • 专为程序员编写的英语学习指南 Github
    • https://github.com/yujiangshui/A-Programmers-Guide-to-English
  • awesome-interview-questions Github
    • https://github.com/MaximAbramchuck/awesome-interview-questions
  • Startups about artificial intelligence. (DM, ML, NLP, CV...) Github
    • https://github.com/majikarp/awesome-programming-books#id-p2
  • Awesome Programming Books Github
    • https://github.com/1c7/crash-course-computer-science-chinese
  • 计算机速成课(全40集) Github
    • https://github.com/1c7/crash-course-computer-science-chinese
  • 清华大学计算机系课程攻略 Github
    • https://github.com/PKUanonym/REKCARC-TSC-UHT
  • 北京大学课程资料整理 Github
    • https://github.com/USTC-Resource/USTC-Course
  • 中国科学技术大学课程资源 Github
    • https://github.com/USTC-Resource/USTC-Course
  • 上海交通大学课程资料分享 Github
    • https://github.com/QSCTech/zju-icicles
  • 浙江大学课程攻略共享计划 Github
    • https://github.com/24OI/OI-wiki
  • 编程竞赛 OI Wiki Github
    • https://github.com/jwasham/coding-interview-university
  • A complete computer science study plan to become a software engineer. Github
    • https://github.com/dipakkr/A-to-Z-Resources-for-Students
  • Curated list of resources for college students Github
    • https://github.com/dipakkr/A-to-Z-Resources-for-Students
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