[{"data":1,"prerenderedAt":138},["ShallowReactive",2],{"maker-irsina":3},[4,31,48,70,87,104,120],{"id":5,"name":6,"line":7,"ai":8,"cat":9,"year":10,"points":11,"comments":12,"rec":13,"s":14,"top":15,"kw":16,"maker":21,"domain":22,"tier":23,"attempts":24,"strip":25,"url":26,"mix":27,"praise":-1,"objection":30,"sub":19},14628636,"3D-convolutional-speaker-recognition","Using 3D Convolutional Neural Networks for Speaker Verification",false,"ai",2017,59,5,"quiet",null,32,[17,18,19,20],"speaker verification","convolutional neural network","speaker recognition","deep learning","irsina","github.com","notable",2,"01030","https:\u002F\u002Fgithub.com\u002Fastorfi\u002F3D-convolutional-speaker-recognition",[28,29,28,29],0,1,"Not compared against NIST Speaker Recognition Evaluation benchmarks; dataset unknown in the literature",{"id":32,"name":33,"line":34,"ai":8,"cat":9,"year":10,"points":35,"comments":36,"rec":13,"s":14,"top":37,"kw":38,"maker":21,"domain":22,"tier":42,"attempts":28,"strip":43,"url":44,"mix":45,"praise":46,"objection":-1,"sub":47},14775065,"Lip Reading","Who Said What? Answered by Deep Learning",13,6,69,[39,40,20,41],"lip reading","audio visual","speaker matching","shown","305000","https:\u002F\u002Fgithub.com\u002Fastorfi\u002F3D-convolutional-Audio-Visual",[29,29,28,28],"Interesting project","audio-visual speech recognition",{"id":49,"name":50,"line":51,"ai":8,"cat":52,"year":10,"points":53,"comments":54,"rec":55,"s":56,"top":57,"kw":58,"maker":21,"domain":22,"tier":23,"attempts":28,"strip":63,"url":64,"mix":65,"praise":67,"objection":68,"sub":69},15582181,"CNTK-World","Simple Deep Learning Tutorials using Microsoft Cognitive Toolkit","learning_science",126,19,"curious",-0.08,15,[59,20,60,61,62],"cntk","tutorial","microsoft cognitive toolkit","jupyter notebooks","5000013310503303010","https:\u002F\u002Fgithub.com\u002Fastorfi\u002FCNTK-World\u002Fblob\u002Fmaster\u002FREADME.rst",[24,12,28,66],3,"Useful documentation for a hard-to-find framework","Installation is difficult and error-prone","deep learning tutorials",{"id":71,"name":72,"line":73,"ai":8,"cat":52,"year":74,"points":75,"comments":36,"rec":13,"s":14,"top":76,"kw":77,"maker":21,"domain":22,"tier":23,"attempts":28,"strip":81,"url":82,"mix":83,"praise":84,"objection":85,"sub":86},17098620,"Easy TensorFlow","Simple and comprehensive tutorials in Deep Learning using TensorFlow",2018,157,12,[78,20,79,80],"tensorflow tutorials","machine learning","tensorflow examples","300305","https:\u002F\u002Fgithub.com\u002Feasy-tensorflow\u002Feasy-tensorflow",[29,29,29,28],"Well-written, well-commented pure TensorFlow tutorials are rare and valuable","Tutorials lack coverage of data loading with tf.Data","tutorials",{"id":88,"name":89,"line":90,"ai":8,"cat":52,"year":74,"points":91,"comments":36,"rec":13,"s":14,"top":92,"kw":93,"maker":21,"domain":22,"tier":97,"attempts":24,"strip":98,"url":99,"mix":100,"praise":101,"objection":102,"sub":103},18211251,"TensorFlow-Course","Comprehensive Tutorials in Deep Learning Using TensorFlow",327,4,[20,94,95,96],"tensorflow","machine learning tutorial","logistic regression","legend","330550","https:\u002F\u002Fgithub.com\u002Fopen-source-for-science\u002FTensorFlow-Course",[24,24,28,28],"Good compilation of recipes and tutorials","Math equations render poorly on GitHub","tutorial course",{"id":105,"name":106,"line":107,"ai":8,"cat":9,"year":74,"points":108,"comments":109,"rec":55,"s":110,"top":36,"kw":111,"maker":21,"domain":22,"tier":97,"attempts":12,"strip":114,"url":115,"mix":116,"praise":117,"objection":118,"sub":119},18265074,"lip-reading-deeplearning","Lipreading with Deep Learning",258,31,0.09,[112,20,39,40,113],"lipreading","cnn","5000000000000001100005035330330","https:\u002F\u002Fgithub.com\u002Fastorfi\u002Flip-reading-deeplearning",[66,12,28,24],"Fascinating and potentially useful application such as sign language","Code matches audio to video rather than recognizing speech, so it isn't really lipreading","computer vision lipreading",{"id":121,"name":122,"line":123,"ai":8,"cat":52,"year":124,"points":125,"comments":126,"rec":127,"s":128,"top":92,"kw":129,"maker":21,"domain":22,"tier":97,"attempts":66,"strip":133,"url":134,"mix":135,"praise":136,"objection":137,"sub":95},19886754,"Python Machine Learning","A Crash Course",2019,350,20,"roasted",-0.06,[130,95,131,132],"python machine learning","scikit-learn","machine learning course","05000001000531000001","https:\u002F\u002Fgithub.com\u002Fmachinelearningmindset\u002Fmachine-learning-course",[24,28,29,66],"Nice, code-focused tutorial series","Tutorials only use libraries rather than implementing algorithms from primitives",1793991224971]