├── README.md ├── dl ├── CNN_Features_off-the-shelf_an_Astounding_Baseline_for_Recognition_解读.md ├── Deep_Forest_解读.md ├── Deep_Learning_Papers_Reading_Roadmap.md ├── Dynamic_Routing_Between_Capsules_译文.md ├── Notes_on_Convolutional_Neural_Networks.md ├── Revisiting_Unreasonable_Effectiveness_of_Data_in_Deep_Learning_Era.md ├── VGG_VERY_DEEP_CONVOLUTIONAL_NETWORKS_FOR_LARGE-SCALE_IMAGE_RECOGNITION_译文.md ├── arxiv-1707-07435-zh │ ├── 1.md │ ├── 2.md │ ├── 3.md │ ├── README.md │ └── img │ │ ├── fig1.jpg │ │ ├── fig2.jpg │ │ ├── fig3.jpg │ │ ├── fig4.jpg │ │ ├── fig5.jpg │ │ ├── fig6.jpg │ │ ├── img1.png │ │ ├── img10.png │ │ ├── img100.png │ │ ├── img101.png │ │ ├── img102.png │ │ ├── img103.png │ │ ├── img104.png │ │ ├── img105.png │ │ ├── img106.png │ │ ├── img107.png │ │ ├── img108.png │ │ ├── img109.png │ │ ├── img11.png │ │ ├── img110.png │ │ ├── img111.png │ │ ├── img112.png │ │ ├── img113.png │ │ ├── img114.png │ │ ├── img115.png │ │ ├── img116.png │ │ ├── img117.png │ │ ├── img118.png │ │ ├── img119.png │ │ ├── img12.png │ │ ├── img120.png │ │ ├── img121.png │ │ ├── img122.png │ │ ├── img123.png │ │ ├── img124.png │ │ ├── img125.png │ │ ├── img126.png │ │ ├── img127.png │ │ ├── img128.png │ │ ├── img129.png │ │ ├── img13.png │ │ ├── img130.png │ │ ├── img131.png │ │ ├── img132.png │ │ ├── img133.png │ │ ├── img134.png │ │ ├── img135.png │ │ ├── img136.png │ │ ├── img137.png │ │ ├── img138.png │ │ ├── img139.png │ │ ├── img14.png │ │ ├── img140.png │ │ ├── img141.png │ │ ├── img142.png │ │ ├── img143.png │ │ ├── img144.png │ │ ├── img145.png │ │ ├── img146.png │ │ ├── img147.png │ │ ├── img148.png │ │ ├── img149.png │ │ ├── img15.png │ │ ├── img150.png │ │ ├── img151.png │ │ ├── img152.png │ │ ├── img153.png │ │ ├── img154.png │ │ ├── img155.png │ │ ├── img156.png │ │ ├── img157.png │ │ ├── img158.png │ │ ├── img159.png │ │ ├── img16.png │ │ ├── img160.png │ │ ├── img161.png │ │ ├── img17.png │ │ ├── img18.png │ │ ├── img19.png │ │ ├── img2.png │ │ ├── img20.png │ │ ├── img21.png │ │ ├── img22.png │ │ ├── img23.png │ │ ├── img24.png │ │ ├── img25.png │ │ ├── img26.png │ │ ├── img27.png │ │ ├── img28.png │ │ ├── img29.png │ │ ├── img3.png │ │ ├── img30.png │ │ ├── img31.png │ │ ├── img32.png │ │ ├── img33.png │ │ ├── img34.png │ │ ├── img35.png │ │ ├── img36.png │ │ ├── img37.png │ │ ├── img38.png │ │ ├── img39.png │ │ ├── img4.png │ │ ├── img40.png │ │ ├── img41.png │ │ ├── img42.png │ │ ├── img43.png │ │ ├── img44.png │ │ ├── img45.png │ │ ├── img46.png │ │ ├── img47.png │ │ ├── img48.png │ │ ├── img49.png │ │ ├── img5.png │ │ ├── img50.png │ │ ├── img51.png │ │ ├── img52.png │ │ ├── img53.png │ │ ├── img54.png │ │ ├── img55.png │ │ ├── img56.png │ │ ├── img57.png │ │ ├── img58.png │ │ ├── img59.png │ │ ├── img6.png │ │ ├── img60.png │ │ ├── img61.png │ │ ├── img62.png │ │ ├── img63.png │ │ ├── img64.png │ │ ├── img65.png │ │ ├── img66.png │ │ ├── img67.png │ │ ├── img68.png │ │ ├── img69.png │ │ ├── img7.png │ │ ├── img70.png │ │ ├── img71.png │ │ ├── img72.png │ │ ├── img73.png │ │ ├── img74.png │ │ ├── img75.png │ │ ├── img76.png │ │ ├── img77.png │ │ ├── img78.png │ │ ├── img79.png │ │ ├── img8.png │ │ ├── img80.png │ │ ├── img81.png │ │ ├── img82.png │ │ ├── img83.png │ │ ├── img84.png │ │ ├── img85.png │ │ ├── img86.png │ │ ├── img87.png │ │ ├── img88.png │ │ ├── img89.png │ │ ├── img9.png │ │ ├── img90.png │ │ ├── img91.png │ │ ├── img92.png │ │ ├── img93.png │ │ ├── img94.png │ │ ├── img95.png │ │ ├── img96.png │ │ ├── img97.png │ │ ├── img98.png │ │ └── img99.png ├── arxiv-1709-07604-zh │ ├── 1.md │ ├── 2.md │ ├── 3.md │ ├── 4.md │ ├── 5.md │ ├── README.md │ └── img │ │ ├── fig1.jpg │ │ ├── fig2.jpg │ │ ├── fig3.jpg │ │ ├── fig4.jpg │ │ ├── img1.png │ │ ├── img10.png │ │ ├── img100.png │ │ ├── img101.png │ │ ├── img102.png │ │ ├── img103.png │ │ ├── img104.png │ │ ├── img105.png │ │ ├── img106.png │ │ ├── img107.png │ │ ├── img108.png │ │ ├── img109.png │ │ ├── img11.png │ │ ├── img110.png │ │ ├── img111.png │ │ ├── img112.png │ │ ├── img113.png │ │ ├── img114.png │ │ ├── img115.png │ │ ├── img116.png │ │ ├── img117.png │ │ ├── img118.png │ │ ├── img119.png │ │ ├── img12.png │ │ ├── img120.png │ │ ├── img121.png │ │ ├── img122.png │ │ ├── img123.png │ │ ├── img124.png │ │ ├── img125.png │ │ ├── img126.png │ │ ├── img127.png │ │ ├── img128.png │ │ ├── img129.png │ │ ├── img13.png │ │ ├── img130.png │ │ ├── img131.png │ │ ├── img132.png │ │ ├── img133.png │ │ ├── img134.png │ │ ├── img135.png │ │ ├── img136.png │ │ ├── img137.png │ │ ├── img138.png │ │ ├── img139.png │ │ ├── img14.png │ │ ├── img140.png │ │ ├── img141.png │ │ ├── img142.png │ │ ├── img143.png │ │ ├── img144.png │ │ ├── img145.png │ │ ├── img146.png │ │ ├── img147.png │ │ ├── img148.png │ │ ├── img149.png │ │ ├── img15.png │ │ ├── img150.png │ │ ├── img151.png │ │ ├── img152.png │ │ ├── img153.png │ │ ├── img154.png │ │ ├── img155.png │ │ ├── img156.png │ │ ├── img157.png │ │ ├── img158.png │ │ ├── img159.png │ │ ├── img16.png │ │ ├── img160.png │ │ ├── img161.png │ │ ├── img162.png │ │ ├── img163.png │ │ ├── img164.png │ │ ├── img165.png │ │ ├── img166.png │ │ ├── img167.png │ │ ├── img168.png │ │ ├── img169.png │ │ ├── img17.png │ │ ├── img170.png │ │ ├── img171.png │ │ ├── img172.png │ │ ├── img173.png │ │ ├── img174.png │ │ ├── img175.png │ │ ├── img176.png │ │ ├── img177.png │ │ ├── img178.png │ │ ├── img179.png │ │ ├── img18.png │ │ ├── img180.png │ │ ├── img181.png │ │ ├── img182.png │ │ ├── img183.png │ │ ├── img184.png │ │ ├── img185.png │ │ ├── img186.png │ │ ├── img187.png │ │ ├── img188.png │ │ ├── img189.png │ │ ├── img19.png │ │ ├── img190.png │ │ ├── img191.png │ │ ├── img192.png │ │ ├── img193.png │ │ ├── img194.png │ │ ├── img195.png │ │ ├── img196.png │ │ ├── img197.png │ │ ├── img198.png │ │ ├── img199.png │ │ ├── img2.png │ │ ├── img20.png │ │ ├── img200.png │ │ ├── img201.png │ │ ├── img202.png │ │ ├── img203.png │ │ ├── img204.png │ │ ├── img205.png │ │ ├── img206.png │ │ ├── img207.png │ │ ├── img208.png │ │ ├── img209.png │ │ ├── img21.png │ │ ├── img210.png │ │ ├── img211.png │ │ ├── img212.png │ │ ├── img213.png │ │ ├── img214.png │ │ ├── img215.png │ │ ├── img216.png │ │ ├── img217.png │ │ ├── img218.png │ │ ├── img219.png │ │ ├── img22.png │ │ ├── img220.png │ │ ├── img221.png │ │ ├── img222.png │ │ ├── img223.png │ │ ├── img224.png │ │ ├── img225.png │ │ ├── img226.png │ │ ├── img227.png │ │ ├── img228.png │ │ ├── img229.png │ │ ├── img23.png │ │ ├── img230.png │ │ ├── img231.png │ │ ├── img232.png │ │ ├── img233.png │ │ ├── img234.png │ │ ├── img235.png │ │ ├── img236.png │ │ ├── img237.png │ │ ├── img238.png │ │ ├── img239.png │ │ ├── img24.png │ │ ├── img240.png │ │ ├── img241.png │ │ ├── img242.png │ │ ├── img243.png │ │ ├── img244.png │ │ ├── img245.png │ │ ├── img246.png │ │ ├── img247.png │ │ ├── img248.png │ │ ├── img249.png │ │ ├── img25.png │ │ ├── img250.png │ │ ├── img251.png │ │ ├── img252.png │ │ ├── img253.png │ │ ├── img254.png │ │ ├── img255.png │ │ ├── img256.png │ │ ├── img257.png │ │ ├── img258.png │ │ ├── img259.png │ │ ├── img26.png │ │ ├── img260.png │ │ ├── img261.png │ │ ├── img262.png │ │ ├── img263.png │ │ ├── img264.png │ │ ├── img265.png │ │ ├── img266.png │ │ ├── img267.png │ │ ├── img268.png │ │ ├── img269.png │ │ ├── img27.png │ │ ├── img270.png │ │ ├── img271.png │ │ ├── img272.png │ │ ├── img273.png │ │ ├── img274.png │ │ ├── img275.png │ │ ├── img276.png │ │ ├── img277.png │ │ ├── img278.png │ │ ├── img279.png │ │ ├── img28.png │ │ ├── img280.png │ │ ├── img281.png │ │ ├── img282.png │ │ ├── img283.png │ │ ├── img284.png │ │ ├── img285.png │ │ ├── img286.png │ │ ├── img287.png │ │ ├── img288.png │ │ ├── img289.png │ │ ├── img29.png │ │ ├── img290.png │ │ ├── img291.png │ │ ├── img292.png │ │ ├── img293.png │ │ ├── img294.png │ │ ├── img295.png │ │ ├── img296.png │ │ ├── img297.png │ │ ├── img298.png │ │ ├── img299.png │ │ ├── img3.png │ │ ├── img30.png │ │ ├── img300.png │ │ ├── img301.png │ │ ├── img302.png │ │ ├── img303.png │ │ ├── img304.png │ │ ├── img305.png │ │ ├── img306.png │ │ ├── img307.png │ │ ├── img308.png │ │ ├── img309.png │ │ ├── img31.png │ │ ├── img310.png │ │ ├── img311.png │ │ ├── img312.png │ │ ├── img32.png │ │ ├── img33.png │ │ ├── img34.png │ │ ├── img35.png │ │ ├── img36.png │ │ ├── img37.png │ │ ├── img38.png │ │ ├── img39.png │ │ ├── img4.png │ │ ├── img40.png │ │ ├── img41.png │ │ ├── img42.png │ │ ├── img43.png │ │ ├── img44.png │ │ ├── img45.png │ │ ├── img46.png │ │ ├── img47.png │ │ ├── img48.png │ │ ├── img49.png │ │ ├── img5.png │ │ ├── img50.png │ │ ├── img51.png │ │ ├── img52.png │ │ ├── img53.png │ │ ├── img54.png │ │ ├── img55.png │ │ ├── img56.png │ │ ├── img57.png │ │ ├── img58.png │ │ ├── img59.png │ │ ├── img6.png │ │ ├── img60.png │ │ ├── img61.png │ │ ├── img62.png │ │ ├── img63.png │ │ ├── img64.png │ │ ├── img65.png │ │ ├── img66.png │ │ ├── img67.png │ │ ├── img68.png │ │ ├── img69.png │ │ ├── img7.png │ │ ├── img70.png │ │ ├── img71.png │ │ ├── img72.png │ │ ├── img73.png │ │ ├── img74.png │ │ ├── img75.png │ │ ├── img76.png │ │ ├── img77.png │ │ ├── img78.png │ │ ├── img79.png │ │ ├── img8.png │ │ ├── img80.png │ │ ├── img81.png │ │ ├── img82.png │ │ ├── img83.png │ │ ├── img84.png │ │ ├── img85.png │ │ ├── img86.png │ │ ├── img87.png │ │ ├── img88.png │ │ ├── img89.png │ │ ├── img9.png │ │ ├── img90.png │ │ ├── img91.png │ │ ├── img92.png │ │ ├── img93.png │ │ ├── img94.png │ │ ├── img95.png │ │ ├── img96.png │ │ ├── img97.png │ │ ├── img98.png │ │ ├── img99.png │ │ └── title.jpg ├── graph-emb │ └── deep-learning-on-graph-a-survey │ │ ├── 5.md │ │ └── img │ │ ├── eq35.png │ │ ├── eq36.png │ │ ├── eq37.png │ │ ├── eq38.png │ │ ├── eq39.png │ │ ├── eq40.png │ │ ├── eq41.png │ │ ├── eq42.png │ │ ├── eq43.png │ │ ├── eq44.png │ │ ├── eq45.png │ │ ├── eq46.png │ │ ├── eq47.png │ │ ├── eq48.png │ │ ├── eq49.png │ │ ├── eq50.png │ │ └── pic7.png ├── more │ ├── caffe2-tut.md │ ├── 使用马尔可夫生成对抗网络进行预先计算的实时纹理合成.md │ ├── 图像识别领域的深度残差学习.md │ ├── 基于R-FCN的物体检测.md │ ├── 基于感知损失函数的实时风格转换和超分辨率重建.md │ ├── 实例正则化：快速风格化缺失的成分.md │ ├── 拥挤场景中的端到端人物检测.md │ ├── 用于肺部CT肺结节分类的深度特征学习.md │ ├── 用于语义分割的全卷积网络.md │ └── 纹理网络：在前馈网络中进行纹理合成与风格化.md ├── vae-tut │ └── 1.md ├── 一个艺术风格化的神经网络算法.md ├── 一文详解_Word2vec_之_Skip-Gram_模型 │ ├── 实现篇.md │ ├── 结构篇.md │ └── 训练篇.md ├── 从_Seq2seq_到_Attention_模型到_Self_Attention（一）.md ├── 从_Seq2seq_到_Attention_模型到_Self_Attention（二）.md ├── 修改一个像素，就能让神经网络识别图像出错.md ├── 卷积神经网络中的每一个过滤器提取一个特定的特征.md ├── 基于机器学习的 Webshell 发现技术探索.md ├── 深度学习_100_题 │ ├── README.md │ └── img │ │ ├── 01d3c1f3e2734ac096645fb628b8b382.jpeg │ │ ├── 044f240c4ebc4d9b8e1ea5e78d6f2325.jpeg │ │ ├── 10432bb4844e4e4ba2f5ff29421f46e1.jpeg │ │ ├── 10f4ed00e2ed469d844bdc8331facdd1.jpeg │ │ ├── 17bbb8adc5e845e7bf84835e68be4c28.jpeg │ │ ├── 18d522717c974d9aac99b68177f092cf.jpeg │ │ ├── 1ebb2a1bbc514399b8c0e1440ccc9c86.jpeg │ │ ├── 1f917097e8a74057b79fe09a648914b3.jpeg │ │ ├── 1f9d59aecc3548a8b2b2d5939e3c177b.jpeg │ │ ├── 200a8082bed943dd83db8b251821fbb4.jpeg │ │ ├── 237042823fe04727a3d359ff5a5065b1.jpeg │ │ ├── 28443a7f3cce47a3958547289f017f11.jpeg │ │ ├── 294feabe2c814b4f826fa9528db78757.jpeg │ │ ├── 2b4627175c78418f9677cb12452f6b46.jpeg │ │ ├── 2ceaf204e1e7430a9eedcd80dfc28933.jpeg │ │ ├── 31d31c9d400743f9b2bb420efa157431.jpeg │ │ ├── 373d350c50a345d7a36a4c1f44479fb9.jpeg │ │ ├── 3bff56564f2747779c026097783a8f4e.jpeg │ │ ├── 40ea5077c9f24110abcf399fe8be542c.jpeg │ │ ├── 4216de73838e4d34a2e44da2ad786718.jpeg │ │ ├── 45501d84d6514fd5ae93fd95dcd41f47.jpeg │ │ ├── 470a8783462d47fe840e949b44f690b8.jpeg │ │ ├── 478263c8d4b941baaa25ce732979673d.jpeg │ │ ├── 48aaf3f4c0e94f26a90ec91573e46738.jpeg │ │ ├── 4a8550697c6a4fe6a806c4114d72d5f1.jpeg │ │ ├── 4dbb0258b1954bdabf2b3edce47b994a.jpeg │ │ ├── 4e845ab031f54096b4fa4d2b66d029f1.jpeg │ │ ├── 5025dae1b5c94900b236fad22861181b.jpeg │ │ ├── 5569533488e14ed2859c70165f460eea.jpeg │ │ ├── 571436d4db2b49148c7f47ba9d0733c5.jpeg │ │ ├── 5b998395ea4849c680497605dca867ff.jpeg │ │ ├── 5d848274a158460ba56d4f3473e8ae0a.jpeg │ │ ├── 601e40b1d39049e89ac3222526c714e3.jpeg │ │ ├── 601e6bf7bc7c47e68f79f0fb8cf7884f.jpeg │ │ ├── 64bc01834f1e4b879610055a22c399ef.jpeg │ │ ├── 6ca0fb53d0dc4a6ebe111b29363b9467.jpeg │ │ ├── 6d438c73742d466ca800a83d9885cd2c.jpeg │ │ ├── 7227e94f7bfc479c835f1d02b8f77848.jpeg │ │ ├── 74defa6e1c494292bc4db925bc35b6f4.jpeg │ │ ├── 786533b5e4454aa5a5a84cd24ccef6b7.jpeg │ │ ├── 79bb290c4aa94db69f4691e21c251963.jpeg │ │ ├── 7bfda32cdba949478f9cd65ad9ac94cc.jpeg │ │ ├── 835339d09d50476cafb63d84cfd2569e.jpeg │ │ ├── 8474177f8e24423f88834be3aca80c9d.jpeg │ │ ├── 87dd5af195e5407f87d9e1f377661fa2.jpeg │ │ ├── 920891b2f82942d09da73cc3cabb51b3.jpeg │ │ ├── 9540565bbfa048d19be41733f4050a10.jpeg │ │ ├── 98aea1cf17d447fa8f8286ab749450dd.jpeg │ │ ├── 9e09a99bb5434718b3d9600e945ab3d8.jpeg │ │ ├── 9ef159838efb41b2bda2605b50ae3374.jpeg │ │ ├── a534357c0d06465a96e490e77c17f6bb.jpeg │ │ ├── ab100e7bfd644f0897d14b6cf3f5b8ca.jpeg │ │ ├── abb75c5177f84329a975b7b783d1d0c1.jpeg │ │ ├── acebaf90ff3f4872b6109d8c117a0d81.jpeg │ │ ├── b1556de5fec04615867af658d4f42bda.jpeg │ │ ├── b231bec601c348329858b2b5c6c78c78.jpeg │ │ ├── b513efbf6ab94b3097bfe7fcd727eb53.jpeg │ │ ├── b660b5a5fd21470998aed602bc84e3a4.jpeg │ │ ├── bb05decb9e2e44d580682a0feec39db2.jpeg │ │ ├── bc042f10b289425aabdd380ef04de3ed.jpeg │ │ ├── be26a56b1542415a943884dcc34ba6e7.jpeg │ │ ├── be592672ea6045d99183f600042a759f.jpeg │ │ ├── bf44a17dd7f34a4bb9833ec2b7576bdd.jpeg │ │ ├── c19a3b46cb744a73aba2b5e26f935a17.jpeg │ │ ├── c3fc2aff06b34ea9b97f8a8538b0713b.jpeg │ │ ├── c5c91c08e41a48fbac9accf8aa3e4951.jpeg │ │ ├── c947ec9172164ac1a8edad51d93abb2c.jpeg │ │ ├── cb78ab75cb0343d7afde1cd12766f0de.jpeg │ │ ├── d1e1afb6df914096bf96ecb12ba5dec5.jpeg │ │ ├── d21501d398a746c5b1bdaa02e27486ea.jpeg │ │ ├── d2a38794de294b6da261d0cc17c9f2ad.jpeg │ │ ├── d3a0723c2afb43b6b28e3d4154a207d9.jpeg │ │ ├── d48c6d980a6c42f49e3d84e706aa32bf.jpeg │ │ ├── da6bbbc2ed464849b0e1f458228bf7d2.jpeg │ │ ├── dad3b0a7e0f24ca9aa1ebac33de04988.jpeg │ │ ├── df2c711b9dac4f73816da43ea48f20ab.jpeg │ │ ├── e6eba2db1ee94444a668443a17bd0acc.jpeg │ │ ├── ede89985091e4ea891302f14c8d59495.jpeg │ │ ├── ee876f21b0cb430e8d2835c4d1e34a21.jpeg │ │ ├── f44a392f9acd449dac3e4251bfdb4d6a.jpeg │ │ ├── f52abe1fd5184e2f9aa09c9f095ebf61.jpeg │ │ ├── f73f1d879d364ff68e1d6a96207389a1.jpeg │ │ ├── f8ebbd9c386f4e25b170f2d1a1632c9e.jpeg │ │ ├── f9b8aeb4296942369cf3cb9efccabae3.jpeg │ │ └── fbf7629a8dc245bebf9646280b6485c4.jpeg ├── 深度学习论文翻译，包括分类论文，检测论文等.md ├── 献给新手的深度学习综述.md ├── 理解_LSTM_网络.md ├── 神经网络调试入门.md ├── 自然语言处理的神经网络模型入门 │ ├── 1.md │ ├── 2.md │ ├── 3.md │ ├── 4.md │ ├── 5.md │ ├── 6.md │ ├── 7.md │ ├── 8.md │ └── img │ │ ├── 0-1.jpg │ │ ├── 1.jpg │ │ ├── 2.jpg │ │ ├── 3.jpg │ │ ├── algo-1.jpg │ │ ├── algo-3.jpg │ │ ├── algo-4.jpg │ │ ├── algo2.jpg │ │ ├── algo5.jpg │ │ ├── tex-1.jpg │ │ ├── tex-10.jpg │ │ ├── tex-11.jpg │ │ ├── tex-12.jpg │ │ ├── tex-13.jpg │ │ ├── tex-14.jpg │ │ ├── tex-15.jpg │ │ ├── tex-16.jpg │ │ ├── tex-17.jpg │ │ ├── tex-18.jpg │ │ ├── tex-19.jpg │ │ ├── tex-2.jpg │ │ ├── tex-20.jpg │ │ ├── tex-21.jpg │ │ ├── tex-22.jpg │ │ ├── tex-23.jpg │ │ ├── tex-24.jpg │ │ ├── tex-25.jpg │ │ ├── tex-26.jpg │ │ ├── tex-27.jpg │ │ ├── tex-28.jpg │ │ ├── tex-29.jpg │ │ ├── tex-3.jpg │ │ ├── tex-30.jpg │ │ ├── tex-31.jpg │ │ ├── tex-32.jpg │ │ ├── tex-33.jpg │ │ ├── tex-34.jpg │ │ ├── tex-35.jpg │ │ ├── tex-36.jpg │ │ ├── tex-37.jpg │ │ ├── tex-4.jpg │ │ ├── tex-5.jpg │ │ ├── tex-6.jpg │ │ ├── tex-7.jpg │ │ ├── tex-8.jpg │ │ └── tex-9.jpg ├── 详解_BiLSTM_及代码实现.md └── 超越ImageNet：谷歌内建300M图像数据集揭露精度与数据的线性增长关系.md ├── img └── 1707-02968-0.jpg ├── interview ├── README.md ├── zhihu-p-35978758.md ├── zhihu-p-35999853.md ├── zhihu-p-36025191.md └── zhihu-p-36113785.md ├── kaggle ├── Bag_of_Words_Meets_Bags_of_Popcorn │ ├── 0.md │ ├── 1.md │ ├── 2.md │ ├── 3.md │ └── README.md └── 如何在 Kaggle 首战中进入前 10%.md ├── keras ├── README.md └── 使用_Python_和_Keras_逐步开发你的第一个神经网络.md ├── matplotlib ├── python-programming-net-matplotlib.md └── rougier-matplotlib-tut.md ├── meta └── 你的机器学习论文严谨吗？青年学者痛批学界“歪风”.md ├── misc ├── Python_爱好者社区历史文章列表（2018.7.13）.md ├── 矩阵求导术（上）.md └── 矩阵求导术（下）.md ├── ml ├── BAT_机器学习_1000_题 │ ├── 1-100.md │ ├── 101-200.md │ ├── 201-300.md │ ├── 301-400.md │ ├── 401-500.md │ ├── 501-600.md │ ├── 601-700.md │ └── img │ │ ├── 004eea92a24f4182800bba86abe6943e.webp │ │ ├── 022b2635846445829146c978e7369c28.webp │ │ ├── 02c224dfc0fc49e39c39bf3fa4fbc78f.webp │ │ ├── 05c7aea7819142ad8c185ebba05761c2.webp │ │ ├── 0671f0a6a032462c8b4d5e02210d28da.webp │ │ ├── 06b91aad62254644b2999209ced2f929.webp │ │ ├── 072e060c78044b0a90d4c8c8c45534c5.webp │ │ ├── 08a5b921375348acb34a0df55dd01a98.webp │ │ ├── 090cbd2adaee45448f822e6b5bcbac11.webp │ │ ├── 0a7b35e226844184aff6accfdb9ac722.webp │ │ ├── 0b01984c3ddb4dddb79273d66d8111cc.webp │ │ ├── 0e320faa94a8436c81652ccdfbf3a5a2.webp │ │ ├── 0e343c7518b74338982b7128c4ce15ee.webp │ │ ├── 1203b462c0294dee9805fc561123519e.webp │ │ ├── 149074283528498ab3f8840ad6930d00.webp │ │ ├── 15ff4396673844e980e4a6ac3260e997.webp │ │ ├── 166af6fae04b4ee49b24b5613da33a39.webp │ │ ├── 18822a5b0d924f9eb51d6d65028f4bf2.webp │ │ ├── 1905ee5081704377932e83ad550afa8c.webp │ │ ├── 1a239ff547054f6c9f0b2dcd34a35d26.webp │ │ ├── 1b18db16975a4fd481b948a68f5af076.webp │ │ ├── 1db0d2b3929b40a09a9794d64c3d8ce8.webp │ │ ├── 207346701baa49779d04f2cf4d1df63d.webp │ │ ├── 20a558cf7b9b414687d7933fea3cc1bb.webp │ │ ├── 215a8e103d044bb083a928d98620bff7.webp │ │ ├── 218653259dcb43d4874d3ca95f024b15.webp │ │ ├── 22854eb7e40546d2af5a9e44c555ef2e.webp │ │ ├── 234d4e95f22a4611b633764f16c43b3b.webp │ │ ├── 26309549267c4387a32cc327f36194d8.webp │ │ ├── 26855aa019d640bfb58049b5620bb3a2.webp │ │ ├── 26d8421fd2fc4de7a08156a869262ef1.webp │ │ ├── 2a1135ba01fb4094854dead542b4b28e.webp │ │ ├── 2b224e77e81045ce8956d5cec11cf74b.webp │ │ ├── 2e41f563cd8d43c68b8262b705e2b38e.webp │ │ ├── 2ed829b34b1e4b75b5216ce672d2ce83.webp │ │ ├── 301659b9b503496c9f7615ed8572ea43.webp │ │ ├── 3abd4914e1f2459fa178e9ea38da268d.webp │ │ ├── 3b39fe17844c40e398b17266d9de83ac.webp │ │ ├── 3b5256e08acd4912ae255dd73d195461.webp │ │ ├── 3cb2bdacf11f46adb3b872d50c449420.webp │ │ ├── 3d10b9e38bc84828829b8f4997df881f.webp │ │ ├── 3f00df53006844e38bb1877788f699d5.webp │ │ ├── 3f12a27e6ea84be4b621dcbe59c96697.webp │ │ ├── 44c02e36bc4644d6867e155a681d904a.webp │ │ ├── 457d447766b74e7f878bd5f73b3902f6.webp │ │ ├── 46cec1477f924dd39d84d283cd5e8128.webp │ │ ├── 4720e74ac74c47cda8d45870c1ba515d.webp │ │ ├── 4aeaf798e6d84f4da9a73ac15deea10d.webp │ │ ├── 511e0a93514f4ff1a20f50f8a0af579c.webp │ │ ├── 51ff9eded6da4c77b12f639ab1a2e46c.gif │ │ ├── 55b92866a5fa42558afac1beed8403fe.webp │ │ ├── 56f3c3f70ffb4908a71823bf52f0dd18.webp │ │ ├── 572599e829ae4e7ca3cb2ce57e3d0c25.webp │ │ ├── 579dcb25f9aa4f43aebb2672372fd63d.webp │ │ ├── 57cc9f5771cb4fd891ac5f86cf0f2134.webp │ │ ├── 5969e09cd71044f891426bc2525ee37f.webp │ │ ├── 5a05638c2669454ab45dbdf8e2580a9a.webp │ │ ├── 65066e0999a04b0db4e6e63985eb9df7.webp │ │ ├── 67d9dfa52b934bcda65fee198a4d47cb.webp │ │ ├── 68f5bf4645e84b7b959dc38e69ee3c9a.webp │ │ ├── 69da2244b7514fb48d3aafac362d400b.webp │ │ ├── 6a0db5b49bb94d2d89575096c227d533.webp │ │ ├── 6a821237173945b9909d2044d8571c61.webp │ │ ├── 6cbb0a66eeb34586813fab85efac1c6e.webp │ │ ├── 7116cf339ccc40aaa4fc91bcb217dc07.webp │ │ ├── 732c9fc493ac4ed5b2b0c0a40651d9f6.webp │ │ ├── 733e455182c241a0aec9e8e5d7b65fa7.webp │ │ ├── 750a1ee8db0d44d49a0bec6c492761c8.webp │ │ ├── 753f65d206b349fca060f745499a20d6.webp │ │ ├── 768a835c279c437d82efcffb886540a1.webp │ │ ├── 76e70b4496954d09b71950fa5ee29472.webp │ │ ├── 778f1b15b4c74bf2bec5ccd423b274af.webp │ │ ├── 7a04300704ec481b857b23d5cb1caf01.webp │ │ ├── 7b200fcd7089458f9bfd91e9182d5526.webp │ │ ├── 7bb320c78b524a6bb270b07709e90be0.webp │ │ ├── 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958a940f485947d397dc900b70cf9cb8.webp │ │ ├── 9892eada12f34e0cb477a7285a3b0b3f.webp │ │ ├── 9b18c221b7d74b2aaabbf2626a71fcfd.webp │ │ ├── 9c27cc2aba624ac69a8bf1f8f786ab58.webp │ │ ├── 9d25fc68e37548f1b8655a0b00619a74.webp │ │ ├── 9d7ee63881d741fab21c673cbb05646a.webp │ │ ├── 9e41bd4f9dd94ab2b2ebcf0bd641d773.webp │ │ ├── a0b26fda137242f6abd241e0b49abcb4.webp │ │ ├── a0cd316354d8455892287c71bfcadda6.webp │ │ ├── a0ee1d3c9360412ea3f9e5fbc97bfbc3.webp │ │ ├── a12a016840fe40b89ce8dba41c871af3.webp │ │ ├── a4bcb3cc4ca2491b8368204137637438.webp │ │ ├── a60d03c814de45a9a05231e6007be1ce.webp │ │ ├── a67170f9a69040858fa487768f3b9b7a.webp │ │ ├── a676516b03e943e1ade1f7bcd392317c.webp │ │ ├── a85af1539ca84bc48b8856a5d1e63726.webp │ │ ├── ab052957c9d7491291a27516e2429a53.webp │ │ ├── ab6a0451dd8e4cc78a778d4d802191d1.webp │ │ ├── ab737c6d6e7e48b0a5083d39b5844405.webp │ │ ├── ac03dc51e78a48e587af03d8610d7bf6.webp │ │ ├── ae2067813593421c9394e92b3313748e.webp │ │ ├── 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d0afeed4097d4e67800f10d3c3691600.webp │ │ ├── d473a20e5c8c4605bb4cd9a0073c31d8.webp │ │ ├── d79ec50f4298444caa995565fd09adfb.webp │ │ ├── d93b260f13e641308c430fa8af868fab.webp │ │ ├── d969e1c730b54faf9d2f3e91899de79b.webp │ │ ├── da3d3de5963147f3aec6ef1cd0d9fd1e.webp │ │ ├── dad0457c2c68420abcb0fd1ce2e47186.webp │ │ ├── dd21506dbc0c47c2a7d143db15d901e5.webp │ │ ├── dfd2ee61759548948ed99ab085ce9253.webp │ │ ├── dfe1c645e1774fd9b74ce2d22da65835.webp │ │ ├── e894f53e1a2f4dc5b1831dee405d8660.webp │ │ ├── e93cf895a5274f94b6c6bc363d1c3c22.webp │ │ ├── e9974841782347b6a4e215b41f7351c3.webp │ │ ├── ea63cb1546d849a0bd578aaa515fb047.webp │ │ ├── ece42ce64b174a9cacb4278ad4c7e2e5.webp │ │ ├── f424acd4bbe8456ab563200da0c0b1f6.webp │ │ ├── f46812b98d184b76afdb3dd96868ce4e.webp │ │ ├── f6a37432cac546fb87d90eafa806ecfb.webp │ │ ├── fb8380b10f1e409cabae40dec650f7c3.webp │ │ ├── fca8076e070e4619a3f3b024fad73949.webp │ │ ├── fce066acc10d4ca783be37a6a606877f.webp │ │ └── fe2587eec4354ee6a10ae1d1f8ed725b.webp ├── graph-emb │ ├── BINE-笔记.md │ ├── DeepWalk-笔记.md │ ├── LINE-笔记.md │ ├── img │ │ ├── bine-author.png │ │ ├── bine-eq10.png │ │ ├── bine-eq12.png │ │ ├── bine-eq14.png │ │ ├── bine-eq7.png │ │ ├── bine-eq8-1.png │ │ ├── bine-eq8.png │ │ ├── bine-eq9.png │ │ ├── deepwalk-fig2.png │ │ ├── deepwalk-fig3.png │ │ ├── deepwalk-fig4.png │ │ ├── node2vec-eq1-1.png │ │ ├── node2vec-eq1-2.png │ │ ├── node2vec-eq1.png │ │ ├── node2vec-eq2-1.png │ │ ├── node2vec-eq2-2.png │ │ ├── node2vec-eq2.png │ │ ├── node2vec-fig2.png │ │ ├── node2vec-tab1.png │ │ ├── pte-eq1.png │ │ ├── pte-eq2.png │ │ ├── pte-eq3.png │ │ ├── pte-eq4.png │ │ ├── pte-eq5.png │ │ ├── pte-eq8.png │ │ └── pte-eq9.png │ ├── node2vec-笔记.md │ ├── pte-论文笔记.md │ └── 论文笔记：图嵌入（非深度）.md └── python-programming-net-ml │ ├── 1.md │ ├── 2.md │ ├── 3.md │ ├── 4.md │ ├── README.md │ └── img │ ├── 10-1.png │ ├── 10-2.png │ ├── 10-3.png │ ├── 10-4.png │ ├── 12-1.png │ ├── 12-2.png │ ├── 12-3.png │ ├── 12-4.png │ ├── 13-1.png │ ├── 13-2.png │ ├── 13-3.png │ ├── 13-4.png │ ├── 13-5.png │ ├── 13-6.png │ ├── 15-1.png │ ├── 16-1.png │ ├── 17-1.png │ ├── 2-1.png │ ├── 20-1.png │ ├── 20-2.png │ ├── 20-3.png │ ├── 20-4.png │ ├── 20-5.png │ ├── 20-6.png │ ├── 20-7.png │ ├── 21-1.png │ ├── 21-2.png │ ├── 21-3.png │ ├── 21-4.png │ ├── 22-1.png │ ├── 22-2.png │ ├── 22-3.png │ ├── 22-4.png │ ├── 22-5.png │ ├── 22-6.png │ ├── 22-7.png │ ├── 22-9.png │ ├── 23-1.png │ ├── 23-10.png │ ├── 23-11.png │ ├── 23-12.png │ ├── 23-13.png │ ├── 23-2.png │ ├── 23-3.png │ ├── 23-4.png │ ├── 23-5.png │ ├── 23-6.png │ ├── 23-7.png │ ├── 23-8.png │ ├── 23-9.png │ ├── 24-1.png │ ├── 24-2.png │ ├── 24-4.png │ ├── 24-5.png │ ├── 28-1.png │ ├── 29-1.png │ ├── 29-2.png │ ├── 29-3.png │ ├── 29-4.png │ ├── 29-5.png │ ├── 29-6.png │ ├── 30-1.png │ ├── 30-2.png │ ├── 30-3.png │ ├── 30-4.png │ ├── 30-5.png │ ├── 30-6.png │ ├── 30-7.png │ ├── 30-8.png │ ├── 30-9.png │ ├── 31-1.png │ ├── 31-2.png │ ├── 31-3.png │ ├── 31-4.png │ ├── 31-5.png │ ├── 31-6.png │ ├── 33-1.png │ ├── 33-2.png │ ├── 33-3.png │ ├── 34-1.png │ ├── 34-2.png │ ├── 37-1.png │ ├── 38-1.png │ ├── 38-2.png │ ├── 38-3.png │ ├── 39-1.png │ ├── 41-1.png │ ├── 41-2.png │ ├── 43-1.png │ ├── 43-2.png │ ├── 43-3.png │ ├── 43-4.png │ ├── 43-5.png │ ├── 5-1.png │ ├── 6-1.png │ ├── 7-1.png │ ├── 7-2.png │ ├── 7-3.png │ ├── 7-4.png │ ├── 7-5.png │ ├── 7-6.png │ ├── 8-1.png │ ├── 8-2.png │ ├── 9-1.png │ ├── 9-2.png │ ├── 9-3.png │ └── 9-4.png ├── nltk └── python-programming-net-nltk.md ├── numpy ├── tentative-numpy-tut.md ├── tutorialspoint-numpy.md ├── 计算布林带.md └── 预测今后的北京高考人数.md ├── opencv └── python-programming-net-opencv.md ├── pandas ├── 10-minutes-to-pandas.md ├── learn-pandas │ ├── README.md │ ├── output_16_0.png │ ├── output_29_0.png │ ├── output_40_0.png │ ├── output_40_1.png │ ├── output_40_2.png │ ├── output_40_3.png │ ├── output_42_0.png │ ├── output_42_1.png │ ├── output_42_2.png │ ├── output_42_3.png │ ├── output_43_2.png │ ├── output_55_0.png │ ├── output_58_2.png │ ├── output_62_0.png │ └── output_62_1.png ├── pandas-cookbook.md └── python-programming-net-pandas.md ├── quant ├── python-programming-net-quant.md └── 自创数据集，使用TensorFlow预测股票入门.md ├── scikit └── scipycon-2018-sklearn-tut-zh │ ├── 1.md │ ├── 10.md │ ├── 11.md │ ├── 12.md │ ├── 13.md │ ├── 14.md │ ├── 15.md │ ├── 16.md │ ├── 17.md │ ├── 18.md │ ├── 19.md │ ├── 2.md │ ├── 20.md │ ├── 21.md │ ├── 22.md │ ├── 23.md │ ├── 3.md │ ├── 4.md │ ├── 5.md │ ├── 6.md │ ├── 7.md │ ├── 8.md │ ├── 9.md │ ├── README.md │ └── img │ ├── average-per-class.png │ ├── bag_of_words.svg │ ├── check_env-1.png │ ├── cluster_comparison.png │ ├── clustering-linkage.png │ ├── clustering.png │ ├── cross_validation.svg │ ├── data_representation.svg │ ├── dbscan.png │ ├── feature_union.svg │ ├── grid_search_cross_validation.svg │ ├── hashing_vectorizer.svg │ ├── ipython_help-1.png │ ├── ipython_help-2.png │ ├── ipython_run_cell.png │ ├── iris_setosa.jpg │ ├── iris_versicolor.jpg │ ├── iris_virginica.jpg │ ├── ml_taxonomy.png │ ├── overfitting_underfitting_cartoon.svg │ ├── parallel_text_clf.png │ ├── parallel_text_clf_average.png │ ├── petal_sepal.jpg │ ├── pipeline.svg │ ├── pipeline_cross_validation.svg │ ├── plot_kneigbors_regularization.png │ ├── randomized_search.png │ ├── supervised_scikit_learn.png │ ├── supervised_workflow.svg │ ├── tex1.gif │ ├── tex2.gif │ ├── tex3.gif │ ├── tex4.gif │ ├── tex5.gif │ ├── tex6.gif │ ├── tex7.gif │ ├── train_test_split.svg │ ├── train_test_split_matrix.svg │ ├── train_validation_test2.svg │ └── unsupervised_workflow.svg ├── tf ├── effective-tf.md ├── first_contact_with_tensorFlow │ ├── 0.md │ ├── 1.md │ ├── 2.md │ ├── 3.md │ ├── 4.md │ ├── 5.md │ ├── 6.md │ ├── 7.md │ ├── README.md │ └── cover.png ├── learning-tf-zh │ ├── 1.md │ ├── 2.md │ ├── 3.md │ ├── 4.md │ ├── README.md │ └── img │ │ ├── 2d_grid.png │ │ ├── GPU.jpg │ │ ├── MarshOrchid.jpg │ │ ├── OrchidFlipLR.png │ │ ├── OrchidSlice.png │ │ ├── OrchidTranspose.png │ │ ├── Selection_001.png │ │ ├── basic_graph.png │ │ ├── cube.png │ │ ├── cube_1.png │ │ ├── cube_2.png │ │ ├── digits_sample.png │ │ ├── ezgif.com-video-to-gif.gif │ │ ├── histogram_normal.png │ │ ├── histogram_normal_centered.png │ │ ├── histogram_tensorflow.png │ │ ├── histogram_tensorflow_wider.png │ │ ├── histogram_uniform_large.png │ │ ├── histogram_uniform_small.png │ │ ├── l07loss.png │ │ ├── l08initial.png │ │ ├── map_reduce.png │ │ ├── names_graph.png │ │ ├── outputfolder.png │ │ ├── plotcircles.png │ │ ├── plotcircles_w_points.png │ │ ├── plt.scatter.png │ │ ├── redx.png │ │ ├── scatter.png │ │ ├── scope_graph.png │ │ ├── server-clinet_model.png │ │ ├── t0601_generate.png │ │ ├── tex1.gif │ │ ├── tex10.gif │ │ ├── tex11.gif │ │ ├── tex12.gif │ │ ├── tex2.gif │ │ ├── tex3.gif │ │ ├── tex4.gif │ │ ├── tex5.gif │ │ ├── tex6.gif │ │ ├── tex7.gif │ │ ├── tex8.gif │ │ └── tex9.gif ├── python-programming-net-tf-chatbot.md ├── python-programming-net-tf-object-detection.md ├── 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