NVIDIA Triton Inference Server is a multi-framework, open-source software that is optimized for inference. It supports popular machine learning frameworks like TensorFlow, Open Neural Network Exchange (ONNX) Runtime, PyTorch, NVIDIA TensorRT, and more. It can be used for your CPU or GPU workloads. In this module, you deploy your production model to NVIDIA Triton server to perform inference on a cloud-hosted virtual machine.

Learn to deploy machine learning models as APIs using FastAPI for efficient application integration.

Learn to Deploy Machine Learning Models. Learn about Server and Server less Frameworks Both using Python

Most organizations wish to harness the power of machine learning (ML) to improve their products, but they may not always have the expertise available in-house. This course shows you how to harness the power of ML for use cases using API calls.

The course enables the engineers/data scientist to build and deploy machine learning models into the Azure cloud, just by using Azure CLI commands.

Object detection is used to locate and identify objects in images. You can use Azure AI Custom Vision to train a model to detect specific classes of object in images.

The ability for applications to detect human faces, analyze facial features and emotions, and identify individuals is a key artificial intelligence capability.

Azure Machine Learning studio is a GUI-based integrated development environment for constructing and operationalizing Machine Learning workflow on Azure. Learn how to develop custom object detection models using this service with NVIDIA GPU accelerated virtual machines.

Azure OpenAI Service provides access to OpenAI's powerful large language models such as ChatGPT, GPT, Codex, and Embeddings models. These models enable various natural language processing (NLP) solutions to understand, converse, and generate content. Users can access the service through REST APIs, SDKs, and Azure OpenAI Studio.

Natural language processing (NLP) solutions use language models to interpret the semantic meaning of written or spoken language. You can use the Language Understanding service to build language models for your applications.

Deploy an Azure Sphere device application to monitor ambient conditions for laboratory conditions. The application will monitor the room environment conditions, connect to IoT Hub, and send telemetry data from the device to the cloud. You'll control cloud-to-device communications and undertake actions as needed.

Deploy an Azure Sphere application to monitor ambient conditions for a laboratory. The application will monitor the room environment, connect to Azure IoT Central, and send telemetry data from the device to the cloud. You'll control cloud-to-device communications and undertake actions as needed.