Azure Machine Learning - Public Preview for October

| Four features now available in Public Preview enable you to customize your compute instance experience by using curated or custom environments, collect all model dependencies in a single operation to generate a package than can be move and deployed across environments, label your images at each pixel level with high quality, and conenct and fine-tune Azure OpenAI models with Azure Machine Learning. | | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | [Environment Support on Compute Instance](https://aka.ms/CreateComputeInstance): You can now use the same image when running a full job on a cluster or an experiment on a compute instance. [Model Packaging (v2)](https://aka.ms/AzureML/ModelPackage): You can now build model packages to deploy to Online Endpoints through the Azure Machine Learning inference server or a custom inference server of your choice. [Label pixels in images through Semantic Segmentation](https://aka.ms/LabelPixels): You can now add tags or labels to individual pixels within images, leverage the vendor workforce in labeling the images, and label categories through hierarchical labeling. [New base inference models with finetuning capabilities](https://aka.ms/OAImodels): You can now utilize two new base inference models (Babbage-002 and Davinci-002) and fine-tuning capabilities for three models (Babbage-002, Davinci-002, and GPT-3.5-Turbo). We are adding fine-tuning capabilities to these three models and making them accessible through the Azure Machine Learning model catalog. | * Azure Machine Learning * Azure OpenAI Service * Features * [ Azure Machine Learning](https://azure.microsoft.com/en-gb/products/machine-learning/)