榜单
IT文库
服务器优惠
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Sedna
Sedna What is Sedna? Features Architecture Sedna’s edge-cloud synergy is implemented based on the following capabilities provided by KubeEdge: Component GlobalManager LocalCon... -
Using ML models within OpenSearch
Using ML models within OpenSearch GPU acceleration Related articles Using ML models within OpenSearch Introduced 2.9 To integrate machine learning (ML) models into your Open... -
Using ML models within OpenSearch
Using ML models within OpenSearch GPU acceleration Related articles Using ML models within OpenSearch Generally available 2.9 To integrate machine learning (ML) models into ... -
Using ML models within OpenSearch
Using ML models within OpenSearch GPU acceleration Related articles Using ML models within OpenSearch Introduced 2.9 To integrate machine learning (ML) models into your Open... -
3.15 数值稳定性和模型初始化
3.15 数值稳定性和模型初始化 3.15.1 衰减和爆炸 3.15.2 随机初始化模型参数 3.15.2.1 PyTorch的默认随机初始化 3.15.2.2 Xavier随机初始化 小结 参考文献 3.15 数值稳定性和模型初始化 理解了正向传播与反向传播以后，我们来讨论一下深度学习模型的数值稳定性问题以及模型参数的初始化方法。深度模... -
nn package
nn package Example 1: ConvNet Forward and Backward Function Hooks Example 2: Recurrent Net nn package 译者：@unknown 校对者：@bringtree 我们重新设计了 nn package, 以便与 autograd 完全集成.... -
Kubeflow Versioning Policies
Kubeflow Versioning Policies Kubeflow versioning Application versioning and stable status Kubeflow application matrix Kubeflow SDKs and CLIs Support levels Feedback Kubef... -
Training Loop
Learner, Metrics, and Basic Callbacks Utils function replacing_yield [source] mk_metric [source] save_model [source] load_model [source] class Learner [source] PyT... -
torchvision.transforms
pytorch torchvision transform 对PIL.Image进行变换 class torchvision.transforms.Compose(transforms) class torchvision.transforms.Scale(size, interpolation=2) class torchvision.transfor... -
Stochastic Gradient Descent (SGD)
Stochastic Gradient Descent (SGD) Calculating Gradients Stepping With a Learning Rate An End-to-End SGD Example Step 1: Initialize the parameters Step 2: Calculate the predictio...