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Parent topic: Using a Notebook Instance for AI Development Through JupyterLab
Introduction to Inference After an AI model is developed, you can use it to create an AI application and quickly deploy the application as an inference service. The AI inference capabilities can be integrated into your IT platform by calling APIs.
AI application users Typical AI application users include AI software integrators, hardware vendors, AI deployment personnel, and AI O&M personnel.
AI Application Source: defaults to the generated AI application. AI Application and Version: The current AI application version is automatically selected, which is changeable. Resource Pool: defaults to public resource pools.
Introduction to Team Labeling Generally, a small data labeling task can be completed by an individual. However, team work is required to label a large dataset. ModelArts provides the team labeling function. A labeling team can be formed to manage labeling for the same dataset. The
Speech Paragraph Labeling Model training requires a large amount of labeled data. Therefore, before the model training, label the unlabeled audio files. ModelArts enables you to label audio files. In addition, you can modify the labels of audio files, or remove their labels and label
Named Entity Recognition Named entity recognition assigns labels to named entities in text, such as time and locations. Before labeling, you need to understand the following: A label name can contain a maximum of 32 characters, including letters, digits, hyphens (-), and underscores
AI Application Source: defaults to the generated AI application. AI Application and Version: The current AI application version is automatically selected, which is changeable. Resource Pool: defaults to public resource pools.
AI Application Source: defaults to the generated AI application. AI Application and Version: The current AI application version is automatically selected, which is changeable. Resource Pool: defaults to public resource pools.
AI Application Source: defaults to the generated AI application. AI Application and Version: The current AI application version is automatically selected, which is changeable. Resource Pool: defaults to public resource pools.
AI Application Source: defaults to the generated AI application. AI Application and Version: The current AI application version is automatically selected, which is changeable. Resource Pool: defaults to public resource pools.
Can Such Cameras Use AI Capabilities? A: Yes, the data of non-Huawei cameras can be migrated to the cloud through the GB28181 protocol. VIAS provides the AI capabilities and IVM provides the capability of migrating camera data to the cloud.
Cost Management Cost Composition ModelArts provides the AI tool chain and AI compute power. The cost consists of the resource cost and O&M cost of AI compute power. Cost Allocation ModelArts supports enterprise project management.
Notebook Instances Remotely Through VS Code Connecting to a Notebook Instance Through VS Code Connecting to a Notebook Instance Through VS Code Toolkit Manually Connecting to a Notebook Instance Through VS Code Uploading and Downloading Files in VS Code Parent topic: Using Notebook for AI
Importing Data Import Operation Specifications for Importing Data from an OBS Directory Specifications for Importing the Manifest File Parent topic: Data Management (Old Version to Be Terminated)
Labeling Data Image Classification Object Detection Image Segmentation Text Classification Named Entity Recognition Text Triplet Sound Classification Speech Labeling Speech Paragraph Labeling Video Labeling Parent topic: Data Management (Old Version to Be Terminated)
Team Labeling Introduction to Team Labeling Team Management Member Management Managing Team Labeling Tasks Parent topic: Data Management (Old Version to Be Terminated)
Creating a Training Job Introduction to Training Jobs Using Existing Algorithms to Train Models Using Frequently-used Frameworks to Train Models Using Custom Images to Train Models Parent topic: Training Management (Old Version )
Viewing the Running Records of a Workflow All runtime statuses of a workflow are recorded. On the workflow list page, click the name of the target workflow. On the workflow details page, view all runtime records of the workflow in the left pane. Figure 1 Viewing execution records
Creating a Workflow To create a workflow, define each phase by referring to Creating Workflow Phases. Follow these steps: Sort out scenarios, understand preset steps' functions, and determine the DAG structure. Debug single-phase functions like training or inference on ModelArts.
