Titlebook: Deep Learning with Azure; Building and Deployi Mathew Salvaris,Danielle Dean,Wee Hyong Tok Book 2018 Mathew Salvaris, Danielle Dean, Wee Hy

BRACE

Is Nuclear Deterrence Still Relevant?get an idea of how they would fit into a larger solution. We also provide a step-by-step tutorial for deployment of a CNN to Azure Kubernetes Services (AKS) with GPU nodes as a hands-on guide for one recommended option for building a real-time request–response AI system.

auxiliary

intangibility

連接

濃縮

Microsoft AI Platform by AI. The Microsoft AI Platform runs on the Microsoft Azure cloud computing environment, which provides computing as a utility where you pay for what you use rather than what you own. For more details on the broader Azure Platform, please see the e-book . (Crump & Luijbregts, 2017). The Microsoft

MANIA

Convolutional Neural Networksminal work done by Hubel and Wiesel (1962). They discovered that individual neuronal cells in the visual cortex responded only to the presence of visual features such as edges of certain orientations. From their experiments they deduced that the visual cortex contains a hierarchical arrangement of n

蝕刻術(shù)

Recurrent Neural Networksactor that figures out the optimal hidden-state representation of the input (in this case a vector of feature maps) and a classifier (typically a fully connected layer). This chapter focuses on the hidden-state representation of other forms of data and explores RNNs. RNNs are especially useful for a

膽汁

Generative Adversarial Networkscation to object detection, image segmentation, image similarity, and text analytics (e.g., sentiment analysis, key phrase extraction). GANs, first introduced by Goodfellow et al. (2014), are emerging as a powerful new approach toward teaching computers how to do complex tasks through a generative p

Devastate

Training AI Modelsre larger. That is why if you are serious about deep learning you have to have access to GPUs. In Azure there are a number of ways you can make use of GPUs, on single VMs or in orchestrated clusters of them. In this chapter, we summarize several of the most common methods available as well as the pr

亞當(dāng)心理陰影

Operationalizing AI Modelsmodel does not become useful until it is deployed somewhere and consumed by the end user. This chapter describes the various options available on Azure to deploy your models. We provide general guidelines on what to use and when, but this is by no means an exhaustive guide to the Azure platform. In