Tag · 7 posts
#machinelearning
Using TensorFlow models in Go
Image via http://www.vpnsrus.com In earlier posts, I discussed hosting a deep learning model such as Resnet50 on Kubernetes or Azure Container Instances. The model can then be used as any API which receives input as JSON and returns a result as JSON. Naturally, you can also run the model in offline scenarios and directly from…
aiUsing the Microsoft Face API to detect emotions in photos and video
⚠️ IMPORTANT: the Face API container was retired early 2021. The container image is not available anymore. In a previous post, I blogged about detecting emotions with the ONNX FER+ model. As an alternative, you can use cloud models hosted by major cloud providers such as Microsoft, Amazon and Google. Besides those, there are many…
aiDetecting emotions with FER+
In an earlier post, I discussed classifying images with the ResNet50v2 model. Azure Machine Learning Service was used to create a container image that used the ONNX ResNet50v2 model and the ONNX Runtime for scoring. Continuing on that theme, I created a container image that uses the ONNX FER+ model that can detect emotions in…
aiResNet50v2 classification in Go with a local container
To quickly go to the code, go here. Otherwise, keep reading… In a previous blog post, I wrote about classifying images with the ResNet50v2 model from the ONNX Model Zoo. In that post, the container ran on a Kubernetes cluster with GPU nodes. The nodes had an NVIDIA v100 GPU. The actual classification was done…
aiCreating a GPU container image for scoring with Azure Machine Learning
In a previous post, I discussed how you can add an existing Kubernetes cluster to an Azure Machine Learning workspace. Adding an existing cluster is necessary when the workspace does not support auto creation of a cluster. That is the case when you want to use the Standard_NC6s_v3 virtual machine image. I also used a…
aiAttaching Kubernetes clusters with NVIDIA V100 GPUs to Azure Machine Learning Service
Azure Machine Learning Service allows you to easily deploy compute for training and inference via a machine learning workspace. Although one of the compute types is Kubernetes, the workspace is a bit picky about the node VM sizes. I wanted to use two Standard_NC6s_v3 instances with NVIDIA Tesla V100 GPUs but that was not allowed.…
aiDeploying Azure Cognitive Services Containers with IoT Edge
Introduction Azure Cognitive Services is a collection of APIs that make your applications smarter. Some of those APIs are listed below: Vision: image classification, face detection (including emotions), OCR Language: text analytics (e.g. key phrase or sentiment analysis), language detection and translation To use one of the APIs you need to provision it in an…
analytics