榜单
服务器优惠
AI论文
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Transfer Learning
DL4J’s Transfer Learning API The transfer learning helper Show me the code I. Import a zoo model II. Set up a fine-tune configuration III. Build new models based on VGG16 A.Mod... -
Overview
DataVec: A Vectorization and ETL Library Introductory Video Key Aspects A Few Examples Targeted Vectorization Engines CSV Transformation Engine Schema Transformation Video E... -
Troubleshooting
Troubleshooting Neural Net Training Contents Data Normalization Weight Initialization Number of Epochs and Number of Iterations Learning Rate Policies and Scheduling Activat... -
cuDNN
Using Deeplearning4j with cuDNN Using Deeplearning4j with cuDNN Deeplearning4j supports CUDA but can be further accelerated with cuDNN. Most 2D CNN layers (such as ConvolutionL... -
Why use Keras
Why use Keras? Keras prioritizes developer experience Keras has broad adoption in the industry and the research community Keras makes it easy to turn models into products Keras ... -
Android Classifier
IRIS Classifier Demo DL4JIrisClassifierDemo Setting the Dependencies Setting up the neural network on a background thread Preparing the training data set and user input Buildin... -
Zoo Models
Available models AlexNet Darknet19 FaceNetNN4Small2 InceptionResNetV1 LeNet NASNet ResNet50 SimpleCNN SqueezeNet TextGenerationLSTM TinyYOLO UNet VGG16 VGG19 Xception... -
为什么选择 Keras?
为什么选择 Keras？ Keras 优先考虑开发人员的经验 Keras 被工业界和学术界广泛采用 Keras 可以轻松将模型转化为产品 Keras 支持多个后端引擎，并且不会将你锁定到一个生态系统中 Keras 拥有强大的多 GPU 和分布式训练支持 Keras 的发展得到深度学习生态系统中的关键公司的支持 为什么选择 Keras？ 在... -
为什么选择 Keras?
为什么选择 Keras？ Keras 优先考虑开发人员的经验 Keras 被工业界和学术界广泛采用 Keras 可以轻松将模型转化为产品 Keras 支持多个后端引擎，不会将你锁定到一个生态系统中 Keras 拥有强大的多 GPU 和分布式训练支持 Keras 的发展得到深度学习生态系统中的关键公司的支持 为什么选择 Keras？ 在如今... -
Autoencoders
What are autoencoders? Where’s Restricted Boltzmann Machine? Supported layers AutoEncoder corruptionLevel sparsity BernoulliReconstructionDistribution hasLossFunction Compo...