Overview
Cloud TI Platform serves as a comprehensive machine learning service platform tailored for AI engineers. It facilitates every stage of AI development, spanning from data preprocessing and model construction to training, evaluation, and service deployment. Equipped with a variety of algorithm components and supporting multiple algorithm frameworks, it accommodates a wide range of AI applications.
Benefits
Closed-Loop Model Training
Cloud TI Platform provides a comprehensive machine learning solution, offering a seamless end-to-end workflow encompassing data preprocessing, model creation, training, and evaluation.
AutoML
Cloud TI Platform enables even those new to AI to automatically construct models, greatly simplifying the entire training process. Additionally, the platform’s auto-tuning tool can further optimize parameter tuning efficiency.
Flexible Resource Scheduling
Cloud TI Platform enables CPU/GPU resources to dynamically adapt to varying computing power requirements, offering flexible billing options to minimize expenses and enhance efficiency.
Multiple Learning Frameworks
Cloud TI Platform integrates a diverse array of learning frameworks, including PySpark, Spark, PyTorch, and TensorFlow, catering to developers with varying needs and preferences.
Diversified Algorithms
Cloud TI Platform encompasses a diverse array of machine learning algorithms, including both traditional and deep learning models, catering comprehensively to various niche fields and applications such as image classification, object detection, and natural language processing (NLP). Moreover, it empowers professional users with the flexibility to deploy customized algorithms, offering enhanced freedom and versatility.
Multi-Instance Scheduling
Cloud TI Platform offers the flexibility to schedule instances manually, based on time, batch parameters, or for reruns. This enhanced flexibility minimizes the time and effort required for manual scheduling across various scenarios.
Interactive Modeling
Cloud TI Platform is a dynamic coding environment that seamlessly integrates with various learning frameworks, supporting both Python and R languages. It is linked with TI-SDK for live resource monitoring and incorporates Git for efficient code management.
Data Labeling and Management
Cloud TI Platform enables the creation and administration of datasets encompassing text, image, table, and various other data formats. Users can conveniently preview data specifics online. Moreover, it supports the import of labeled image data in industry-standard Pascal VOC and COCO formats. Labeled data facilitates distribution statistics and visualization.
Convenient Effect Visualization
Cloud TI Platform enables robust visualization and interactive analysis of source data, providing immediate clarity and comprehensive insights. Model training effectiveness is presented intuitively, allowing quick assessments of model quality and optimization strategies without the need to delve into detailed information.
Scenarios
Finance
Industrial Engineering
Education
Financial clients possess a range of business needs. The crucial aspect of improving their efficiency, profits, and user satisfaction is their capacity to suggest optimal financial products to clients using extensive historical data.
Cloud TI Platform aids in constructing predictive models of user purchasing behaviors. This empowers financial organizations to offer more precise recommendations of tailored products to individual users.
Traditional industrial quality inspection methods are labor-intensive, expensive, and susceptible to oversights. The Cloud TI Platform identifies and categorizes product defects using device parameters and production images, revolutionizing quality control by digitizing the process. This not only reduces labor expenses but also minimizes omission rates significantly.
As the AI industry experiences a surge, numerous AI algorithm competitions have emerged. Organizers continually grapple with the challenge of offering a unified tool that accommodates diverse team work habits and simultaneous participation from thousands of contestants. The TI Platform addresses this issue with its wealth of algorithms and framework components, catering to the requirements of various users. Additionally, high-performance, stable clusters are available to support extensive training tasks.
Compute
Edge Computing
Container
Distributed Cloud
Microservice
Serverless
Essential Storage Service
Data Migration
Data Process and Analysis
Relational Database
NoSQL Database
Enterprise Distributed DBMS
Database SaaS Tool
Networking
CDN and Edge platform
Network Security
Data Security
Application Security
Endpoint Security
Business Security
Security Services
Security Management
Domains & Websites
Office Collaboration
Enterprise Applications
Data Analysis
Image Recognition
Face Recognition
Voice Technology
AI Platform Service
Natural Language Processing
Optical Character Recognition
Internet of Things
Message Queue
Middleware
Communication
Interactive Video Services
Stream Services
Media On-Demand
Media Process Services
Media SDK
Cloud Real-time Rendering
Game Services
Game Video Service
Education Services
Blockchain Service
Building Services
Cloud Resource Management
Management and Audit Tools
Developer Tools
Monitor and Operation
Education