January 2019
Beginner to intermediate
576 pages
14h 31m
Chinese
Content preview from 深度學習｜內行人的做法
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第五章：打造深度網路
// 載入訓練資料：
RecordReader rr = new CSVRecordReader();
rr.initialize(new FileSplit(new File(filenameTrain)));
DataSetIterator trainIter = new RecordReaderDataSetIterator(rr,batchSize,0,2);
我們會在迭代器中告訴資料讀取器，我們的資料共有幾個欄位，其中哪個欄位代表的是
標籤。
確定網路的架構
我們需要的是一個基本的多層感知器，而且我們想要用
MultiLayerConfiguration
這個物件
來進行設定（它也可以用來設定任何 DL4J 網路架構），做法如下：
//log.info("Build model....");
MultiLayerConfiguration conf = new NeuralNetConfiguration.Builder()
.seed(seed)
.iterations(1)
.optimizationAlgo(OptimizationAlgorithm.STOCHASTIC_GRADIENT_DESCENT)
.learningRate(learningRate)
.updater(Updater.NESTEROVS).momentum(0.9)
.list()
.layer(0, new DenseLayer.Builder().nIn(numInputs).nOut(numHiddenNodes) ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.