【文件属性】：
文件名称：李宏毅深度学习.zip
文件大小：64.02MB
文件格式：ZIP
更新时间：2021-12-16 11:31:49
深度学习
李宏毅老师的深度学习笔记和部分代码
【文件预览】：
李宏毅深度学习笔记
----ML-notes-html()
--------12_Convolutional-Neural-Network-part2.html(112KB)
--------11_Convolutional-Neural-Network-part1.html(135KB)
--------10_Keras.html(115KB)
--------3_Regression-demo(Adagrad).html(104KB)
--------2_Regression-Case-Study.html(678KB)
--------14_Why-Deep.html(44KB)
--------5_Gradient-Descent.html(356KB)
--------6_Classification.html(338KB)
--------8_Deep-Learning.html(105KB)
--------7_Logistic-Regression.html(495KB)
--------9_Backpropagation.html(446KB)
--------13_Tips-for-Deep-Learning.html(443KB)
--------4_Where-does-the-error-come-from.html(323KB)
--------1_Introduction.html(27KB)
----ML-notes-md()
--------6_Classification.md(22KB)
--------5_Gradient Descent.md(17KB)
--------1_Introduction.md(8KB)
--------12_Convolutional Neural Network part2.md(24KB)
--------10_Keras.md(23KB)
--------9_Backpropagation.md(14KB)
--------8_Deep Learning.md(20KB)
--------13_Tips for Deep Learning.md(49KB)
--------4_Where does the error come from.md(26KB)
--------7_Logistic Regression.md(23KB)
--------3_Regression demo(Adagrad).md(10KB)
--------14_Why Deep.md(24KB)
--------11_Convolutional Neural Network part1.md(35KB)
--------2_Regression Case Study.md(31KB)
----img()
--------results.png(164KB)
--------regularization-illustration.png(619KB)
--------Xcp-2.png(162KB)
--------Xcp-3.png(171KB)
--------learningMap.png(104KB)
--------loss-figure.png(142KB)
--------large-variance.png(344KB)
--------Xcp-overfitting.png(114KB)
--------transfer-Learning.png(831KB)
--------unsupervised-Learning.png(1.68MB)
--------reinforcement-Learning.png(208KB)
--------estimator.png(339KB)
--------Xcp-5.png(175KB)
--------L1L2regularization.png(189KB)
--------cross-validation.png(45KB)
--------best-function.png(96KB)
--------model.png(203KB)
--------pokeman-parameters.png(439KB)
--------semi-supervised-Learning.png(617KB)
--------Xcp-compare.png(135KB)
--------model-bias.png(498KB)
--------new-results.png(212KB)
--------model-selection.png(40KB)
--------goodness-of-function.png(649KB)
--------gradient-stuck.png(379KB)
--------regularization.png(67KB)
--------gradient-two-parameters.png(443KB)
--------n-flod-cross-validation.png(66KB)
--------gradient-descent.png(160KB)
--------bias-variance.png(1.2MB)
--------large-bias.png(114KB)
--------hidden-factors.png(343KB)
--------regularization-performance.png(158KB)
--------bias-vs-variance.png(262KB)
--------new-model.png(86KB)
--------5000-tests.png(436KB)
--------L1-L2.png(181KB)
--------loss-function.png(94KB)
--------Xcp-4.png(161KB)
--------structured-Learning.png(393KB)
----index.html(23KB)
----LICENSE(18KB)
----.DS_Store(6KB)
----ML-notes-pdf()
--------12_Convolutional Neural Network part2.pdf(9.94MB)
--------11_Convolutional Neural Network part1.pdf(5.06MB)
--------2_Regression Case Study.pdf(5.12MB)
--------13_Tips for Deep Learning.pdf(6.78MB)
--------6_Classification.pdf(4.26MB)
--------8_Deep Learning.pdf(2.87MB)
--------10_Keras.pdf(5.42MB)
--------7_Logistic Regression.pdf(3.34MB)
--------5_Gradient Descent.pdf(3.7MB)
--------3_Regression demo(Adagrad).pdf(459KB)
--------9_Backpropagation.pdf(1.54MB)
--------1_Introduction.pdf(3.22MB)
--------14_Why Deep.pdf(4.63MB)
----code()
--------Digits-Detection()
--------.DS_Store(6KB)
--------Gradient-Descent-Demo()
----README.md(5KB)
----keras-tips.md(2KB)