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资源详情
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├
│├
││├HelloWorld-MachineLearningRecipes#1.mp4
││├Let’sWriteaPipeline-MachineLearningRecipes#4.mp4
││├MachineLearningoverCoffeewithaGoogler.mp4
││├VisualizingaDecisionTree-MachineLearningRecipes#2.mp4
││├WhatMakesaGoodFeature--MachineLearningRecipes#3.mp4
││├
│││├HelloWorld-MachineLearningRecipes#1.srt
│││├LetusWriteaPipeline-MachineLearningRecipes#4.srt
│││├MachineLearningoverCoffeewithaGoogler.srt
│││├VisualizingaDecisionTree-MachineLearningRecipes#2.srt
│││└WhatMakesaGoodFeature-MachineLearningRecipes#3.srt
││├
│││└HelloWorld-MachineLearningRecipes#1_chs.srt
│├
││├cs229-lecture01.mp4
││├cs229-lecture02.mp4
││├cs229-lecture03.mp4
││├cs229-lecture04.mp4
││├cs229-lecture05.mp4
││├cs229-lecture06.mp4
││├cs229-lecture07.mp4
││├cs229-lecture08.mp4
││├cs229-lecture09.mp4
││├cs229-lecture10.mp4
││├cs229-lecture11.mp4
││├cs229-lecture12.mp4
││├cs229-lecture13.mp4
││├cs229-lecture14.mp4
││├cs229-lecture15.mp4
││├cs229-lecture16.mp4
││├cs229-lecture17.mp4
││├cs229-lecture18.mp4
││├cs229-lecture19.mp4
││├cs229-lecture20.mp4
││└MachineLearningAllMaterials.zip
│├
││├[斯坦福大学-机器学习课程].materials.rar
││├10特征选择.mp4
││├11贝叶斯统计正则化.mp4
││├12K-means算法.mp4
││├13高斯混合模型.mp4
││├14主成分分析法.mp4
││├15奇异值分解.mp4
││├16马尔可夫决策过程.mp4
││├17离散与维数灾难.mp4
││├18线忄生二次型调节控制.mp4
││├19微分动态规划.mp4
││├1机器学习的动机与应用.mp4
││├20策略搜索.mp4
││├2监督学习应用.梯度下降.mp4
││├3欠拟合与过拟合的概念.mp4
││├4牛顿方法.mp4
││├5生成学习算法.mp4
││├6朴素贝叶斯算法.mp4
││├7最优间隔分类器问题.mp4
││├8顺序最小优化算法.mp4
││└9经验风险最小化.mp4
├
│├
││├Class_8.mp4
││├Class_8.pdf
││├Class_8_Code.rar
││├MacOS_precompiled-WITHOUT_SOURCE-v0.02.tar
││└Windows-Precompiled-RF_MexStandalone-v0.02-.zip
│├
││├Class_2.mp4
││├Class_2.pdf
││└Class_2_Code.rar
│├
││├Class_9.mp4
││├Class_9.pdf
││└Class_9_Code.rar
│├
││├Class_6.mp4
││├Class_6.pdf
││└Class_6_Code.rar
│├
││├Class_7.mp4
││├Class_7.pdf
││└Class_7_Code.rar
│├
││├Class_3.mp4
││├Class_3.pdf
││├Class_3_Code.rar
││└Homework_Dataset.rar
│├
││├Class_12.mp4
││├Class_12.pdf
││└Class_12_Code.rar
│├
││├Class_13.mkv
││├Class_13.pdf
││├Class_13_Code.rar
││└References.rar
│├
││├Class_11.mkv
││├Class_11.pdf
││└Class_11_Code.rar
│├
││├Class_10.mp4
││├Class_10.pdf
││└Class_10_Code.rar
│├
││├Class_4.mp4
││├Class_4.pdf
││├Class_4_Code.rar
││└Homework_Dataset.rar
│├
││├Class_5.mp4
││├Class_5.pdf
││└Class_5_Code.rar
│├
││├Class_1.mp4
││├Class_1.pdf
││├Class_1_Code.rar
││└MATLAB揭秘.pdf
├
│├<25种人工神经网络模型matlab源码>
││├chapter12.png
││├chapter12_01.png
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