机器学习-李宏毅(2019)machinelearning_170_机器学习李宏毅(2019)machinelearning
1 文件名称： 机器学习-李宏毅（2019）machinelearning_170_共：4.22gb 文件总数量： 86条 压缩文件数量： 0条 压缩文件比： 0% 疑似加密文件： 0条(需要授权播放的文件) 文件创建时间： 2020-9-8 12:37:21
目录：【机器学习-李宏毅（2019）machinelearning】目录：【机器学习-李宏毅（2019）machinelearning】9.p9mllecture4_classification.mp486.p47flow-basedgenerativemodel_.mp485.p46elmo84.p45transformer.mp483.p44gan(quickreview)_.mp482.p43networkcompression(6_6).mp481.p43networkcompression(5_6)_.mp480.p43networkcompression(4_6).mp48.p8mllecture2_wheredoestheerrorc.mp479.p43networkcompression(3_6).mp478.p43networkcompression(2_6).mp477.p43networkcompression(1_6)_.mp476.p42mllecture23-3_reinforcementlea_.mp475.p41mllecture23-2_policygradient.mp474.p40mllecture23-1_deepreinforcemen.mp473.p39moreaboutauto-encoder(4_4).mp472.p39moreaboutauto-encoder(3_4).mp471.p39moreaboutauto-encoder(2_4).mp470.p39moreaboutauto-encoder(1_4).mp47.p7thenextstepformachinelearning.mp469.p38mllecture18_unsupervisedlearni.mp468.p37mllecture17_unsupervisedlearni.mp467.p36mllecture16_unsupervisedlearni.mp466.p35metalearning–metric-based(3_3).mp465.p35metalearning–metric-based(2_3).mp464.p35metalearning–metric-based(1_3).mp463.p34metalearning-gradientdescenta.mp462.p34metalearning-gradientdescenta.mp461.p34metalearning-gradientdescenta.mp460.p33mllecture15_unsupervisedlearni.mp46.p6mllecture0-2_whyweneedtolearn.mp459.p32mllecture14_unsupervisedlearni.mp458.p31mllecture13_unsupervisedlearni.mp457.p30metalearning–maml(9_9)_.mp456.p30metalearning–maml(8_9).mp455.p30metalearning–maml(7_9)_.mp454.p30metalearning–maml(6_9)_.mp453.p30metalearning–maml(5_9).mp452.p30metalearning–maml(4_9).mp451.p30metalearning–maml(3_9).mp450.p30metalearning–maml(2_9)_.mp45.p5mllecture1_regression-demo.mp449.p30metalearning–maml(1_9).mp448.p29sequence-to-sequencelearning.mp447.p28lifelonglearning(1_7)_.mp446.p25mllecture22_ensemble.mp445.p24ordered(莊永松).mp444.p23mllecture21-2_recurrentneural_.mp443.p23mllecture21-1_recurrentneural.mp442.p22explainableml_.mp441.p22explainableml(8_8).mp440.p22explainableml(7_8).mp44.p4mllecture3-3_gradientdescent.mp439.p22explainableml(6_8)_.mp438.p22explainableml(5_8)_.mp437.p22explainableml(4_8).mp436.p22explainableml(3_8).mp435.p22explainableml(2_8).mp434.p21mllecture9-3_fizzbuzzintenso.mp433.p20mllecture9-2_kerasdemo2.mp432.p19mllecture9-1_tipsfortraining.mp431.p18attackmlmodels(8_8).mp430.p18attackmlmodels(7_8).mp43.p3mllecture3-2_gradientdescent_.mp429.p18attackmlmodels(6_8).mp428.p18attackmlmodels(5_8).mp427.p18attackmlmodels(4_8).mp426.p18attackmlmodels(3_8).mp425.p18attackmlmodels(2_8).mp424.p18attackmlmodels(1_8)_.mp423.p17mllecture8-3_kerasdemo.mp422.p16mllecture8-2_keras2.0.mp421.p15mllecture8-1_“helloworld”ofd.mp420.p14mllecture10_convolutionalneura.mp42.p2mllecture3-1_gradientdescent.mp419.p13anomalydetection(7_7).mp418.p13anomalydetection(6_7).mp417.p13anomalydetection(5_7)_.mp416.p13anomalydetection(4_7).mp415.p13anomalydetection(3_7).mp414.p13anomalydetection(2_7).mp413.p13anomalydetection(1_7).mp412.p12mllecture7_backpropagation.mp411.p11mllecture6_briefintroductiono.mp410.p10mllecture5_logisticregression.mp41.p1mllecture1_regression-casestud.mp4
