Overview

The AI platform is customer-centric, leveraging independent R&D and continuous technological innovation. Focusing on industry users in security, finance, energy, automotive, and education, it aims to become a leading, high-performance, scalable, and secure enterprise-grade AI platform. The AI platform provides unified resource management and multi-strategy scheduling for heterogeneous computing clusters, visual AI modeling, AI training jobs, and full lifecycle management for AI service deployment.

Using the AI platform, users can conveniently manage training data, develop models, train models, test models, manage models, manage algorithms, and manage workflows. Users can also utilize the platform's comprehensive monitoring capabilities for cluster resources and task status to view task and resource operations in real-time, facilitating a deeper understanding of the entire task execution process.

The User Guide helps users quickly build standardized AI development workflows using the AI platform for algorithm development and training. The guide details how to use mainstream deep learning frameworks like TensorFlow and PyTorch for AI business development on the platform, including creating AI development environments, submitting training jobs, viewing job logs, managing personal data, algorithms, and models, and sharing them for collaboration. It also covers creating workflow jobs. Users can use the AI platform as a one-stop workstation for AI business development to accelerate business innovation.

System Requirements

The AI development platform requires the following software environment:
Client Browser:
Operating System: Windows 10 or later.
Browser: Chrome 86 or later.

Description

The following uses TensorFlow as an example to illustrate how to start AI algorithm development and training jobs using the AI platform. Usage of other frameworks can be referred to in subsequent chapters.