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Introduction to ExeML

ExeML

ModelArts ExeML is a customized code-free model development tool that helps users start AI application development from scratch with high flexibility. ExeML automates model design, parameter tuning and training, and model compression and deployment with the labeled data. Developers do not need to develop basic and encoding capabilities, but only to upload data and complete model training and deployment as prompted by ExeML.

Currently, you can use ExeML to quickly create sound classification, text classification, image classification, predictive analytics, and object detection models. It can be widely used in industrial, retail, and security fields.

  • Image classification classifies and identifies objects in images.
  • Object detection identifies the position and class of each object in images.
  • Predictive analytics classifies or predicts structured data.
  • Sound classification classifies and identifies different sounds in the environment.
  • Text classification identifies the category of a piece of text.

For the example of building a model using the ExeML function, see Service Developers: Using ExeML to Build Models in the ModelArts Getting Started.

ExeML Usage Process

With ModelArts ExeML, you can develop AI models without coding. You only need to upload data, create a project, label the data, publish training, and deploy the trained model. For details, see Figure 1.

Figure 1 Usage process of ExeML

ExeML Projects

  • Image Classification

    An image classification project aims to classify images. You only need to add images and label the images. After the images are labeled, an image classification model can be quickly generated. It can automatically classify offerings, vehicle types, and defective goods. For example, in the quality check scenario, you can upload a product image, label the image as qualified or unqualified, and train and deploy a model to inspect product quality.

  • Object Detection

    An object detection project aims to identify the class and location of objects in images. You only need to add images and label objects in the images with proper bounding boxes. The labled images will be used as the training set for creating a model. The model can identify multiple objects and count the number of objects in a single image, as well as inspect employees' dress code and perform unattended inspection of article placement.

  • Predictive Analytics

    A predictive analytics project is an automated model training application for structured data, which can classify or predict structured data. It can be used for user profile analysis and targeted marketing, as well as predictive maintenance of manufacturing equipment based on real-time data to identify equipment faults.

  • Sound Classification

    A sound classification project identifies whether a certain sound appears in a sound file. It can be used to monitor abnormal sounds in production or security scenarios.

  • Text Classification

    A text classification project identifies the class of a piece of text.