数据科学平台CyberScience
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简介面向开发者和企业的一站式AI数据科学平台，提供交互式和可视化建模服务，算法模型全生命周期管理所属领域大数据、模型平台应用场景AI教育实训CyberScience可以帮助您构建一个安全可靠的人工智能教学实训平台。平台包含丰富课程和案例资源，以拖拽式、低代码方式进行数据处理和可视化分析，为老师和学生提供了AI建模的实验环境，满足高校对内、对外的教学课程设计、实验实训、科研训练等多方面需求。智能推荐引擎使用CyberScience可以对用户、物品、行为和场景信息等多维度数据进行算法处理，快速搭建智能推荐引擎。平台通过对多种推荐算法进行建模，配置实时调度任务，实现智能实时推荐，降低运营人员的人力成本，提高流量的转换率。智能风控系统CyberScience 平台整合大数据体系通过强化算法、算力等人工智能技术对风险进行深度挖掘结合指标、规则、模型、决策流等组合计算，对风控目标进行风险的控制和风险量化提示，高效、准确地实现全链路风险控制的自动化。优势一站式支持一站式机器学习平台能力，只要准备好训练数据集，所有建模工作（包括数据接入、数据预处理、特征分析、模型训练、模型评估、模型发布）都可通过平台实现无代码开发封装100+可视化建模算子，支持无代码化机器学习/深度学习，降低产品使用门槛。灵活建模支持常见的编程语言和多种数据处理方式，支持模型部署 ，满足企业定制化需求多数据源支持结构化、非结构化等5种以上数据库类型，提供20+种数据源接入，灵活切换使用不同数据源深度学习支持主流深度学习框架，并加入 GPU 算力支撑，助力海量数据以及复杂模型的训练及实际应用。产品服务介绍随着AI技术的极速发展，AI能力正在助力产业加速场景化落地。CyberScience是数新网络面向开发者和企业的一站式AI数据科学平台，提供交互式和可视化建模服务，算法模型全生命周期管理。平台可帮助开发者快速开发AI应用，解决本地代码维护不方便、数据传输不安全、模型部署工程难等现实问题，从而提升团队协同效率，以信息化的手段引领技术创新，为客户提供全方位AI管理服务。
### Overview This is a one-stop AI data science platform for developers and enterprises, providing interactive and visual modeling services as well as full-life cycle management for algorithm models. It falls into the fields of big data and model platforms. ### Application Scenarios 1. AI Education and Training CyberScience can help build a safe and reliable artificial intelligence teaching and training platform. The platform is equipped with rich course and case resources, and supports data processing and visual analysis via drag-and-drop and low-code methods, providing an AI modeling experimental environment for teachers and students. It meets the diverse needs of colleges and universities for internal and external teaching curriculum design, experimental training, scientific research training and other aspects. 2. Intelligent Recommendation Engine Using CyberScience, users can perform algorithmic processing on multi-dimensional data including user, item, behavior and scene information to quickly build an intelligent recommendation engine. The platform models multiple recommendation algorithms, configures real-time scheduling tasks to enable intelligent real-time recommendation, reduces labor costs for operation personnel, and improves traffic conversion rate. 3. Intelligent Risk Control System The CyberScience platform integrates big data systems, leverages AI technologies such as enhanced algorithms and computing power to deeply mine risks, and combines indicators, rules, models and decision flows for combined calculation, to conduct risk control and risk quantification prompts for risk control targets, efficiently and accurately realizing the automation of end-to-end risk control. ### Core Advantages 1. One-stop Support As a one-stop machine learning platform, as long as the training dataset is prepared, all modeling work (including data access, data preprocessing, feature analysis, model training, model evaluation, and model release) can be completed via no-code development. It encapsulates over 100 visual modeling operators, supports no-code machine learning/deep learning, and lowers the threshold for product usage. 2. Flexible Modeling It supports common programming languages and multiple data processing methods, and supports model deployment to meet enterprise customized needs. 3. Multi-data Source Support It supports more than 5 database types including structured and unstructured data, provides access to over 20 data sources, and enables flexible switching between different data sources. 4. Deep Learning Support It supports mainstream deep learning frameworks, and is equipped with GPU computing power to support the training and practical application of massive data and complex models. ### Product Service Introduction With the rapid development of AI technology, AI capabilities are accelerating the scenario-based implementation of industrial applications. CyberScience is a one-stop AI data science platform launched by Shuxin Network for developers and enterprises, providing interactive and visual modeling services and full-life cycle management for algorithm models. The platform helps developers quickly develop AI applications, solve practical problems such as inconvenient local code maintenance, unsafe data transmission, and difficult model deployment, thereby improving team collaboration efficiency, leading technological innovation through informatization means, and providing customers with all-round AI management services.
