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WiMi Developed Execution Platform for AutoAIM Analytics to Facilitate Machine Learning in Marketing

WiMi Developed a Real-Time Three-Dimensional Holographic Communication System

WiMi Hologram Cloud a leading global Hologram Augmented Reality (“AR”) Technology provider announced that it developed the AutoAIM (Automatic Artificial Intelligence Marketing) analytical execution platform, which uses visual-based programming to organize ML (Machine Learning) more intuitively, facilitating the application and understanding of ML in marketing.

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WiMi’s AutoAIM implements ML in marketing by creating a real-time repository of projects and making implementation recommendations for ML in marketing. In this repository, users can learn, share and reuse workflows (visualization code). Visual modular coding is a visual representation-based programming approach for extending Machine Learning (ML) in the marketing domain. It organizes ML projects in an intuitive way through configurable nodes. Our visual programming approach is easier to understand and use than traditional script-based coding interfaces.

AutoAIM analysis platform is a software tool based on visual programming. It provides an intuitive interface that allows users to build and design ML projects by dragging and connecting nodes. These nodes represent different functional components such as data preprocessing, feature extraction, model selection and evaluation. Users are free to select and configure these nodes to build their own workflows according to their project needs. To support different marketing needs and approaches, several ML frameworks are used in AutoAIM. These frameworks include methods such as supervised learning, unsupervised learning and deep learning. Users can choose the appropriate framework and algorithm according to their project requirements.

In terms of technical execution, users first need to import and prepare their marketing data. They can use the data preprocessing nodes provided by AutoAIM to perform operations such as data filtering, feature selection and transformation. Next, users can select the appropriate model node and connect it to the data processing node. In the model node, the user can configure the parameters and hyperparameters of the model, as well as select appropriate evaluation metrics. Once the workflow is configured, users can execute the ML project and observe the results. AutoAIM provides visualization tools and charts to help users analyze and interpret the model output. Users can also adjust nodes and parameters in the workflow and optimize as needed.

With our conceptual visual coding and AutoAIM analytical platform, users are able to approach marketing program development more intuitively and flexibly. They can quickly build and adapt workflows without having to delve into the underlying programming language and algorithmic details. This enables marketing teams to better collaborate, share, and reuse workflows to increase productivity and accelerate the execution and development of marketing applications.

The technology and logic of the AutoAIM platform are reflected in the following areas:

Visual programming: the AutoAIM platform uses a visual-based programming approach to transform complex machine learning algorithms and processes into intuitive graphical interfaces and drag-and-drop functionality. This approach enables marketing professionals to quickly create and implement machine learning projects without an in-depth knowledge of programming languages. Users can build their own ML models by combining different modules with simple operations, and make real-time adjustments and optimizations.

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Real-time repository: the AutoAIM platform provides a real-time repository with five annotated sample projects. These projects cover a variety of areas such as customer churn, sentiment analysis, automated image analysis, search engine optimization and customer experience. Users can learn and draw from these examples to understand the application of machine learning in different marketing scenarios, and customize and improve them in their own projects.

Implementation recommendations: more than just a tool for creating and implementing ML projects, the AutoAIM platform provides powerful implementation recommendations. By analyzing data and algorithm performance, the platform is able to provide users with real-time feedback and recommendations. These recommendations can help users optimize their marketing strategies and improve the accuracy and effectiveness of machine learning models.

Workflow sharing and reuse: the AutoAIM platform allows users to learn, share and reuse workflows. Users can save the workflows they create on the platform and share them with other users. This type of knowledge sharing and collaboration promotes learning and exchange among marketing professionals and accelerates the application and innovation of machine learning in marketing.

The AutoAIM platform will significantly drive growth and innovation in the AI marketing space. By streamlining the process of creating and implementing machine learning programs, the platform enables more marketing professionals to leverage AI technology to improve the effectiveness and efficiency of marketing campaigns. Over time, AutoAIM will continue to optimize and expand its platform to meet market needs and continue to lead innovation in the AI marketing.

WiMi’s technical team utilized advanced techniques and algorithms in developing the AutoAIM platform. They have combined the latest research findings in the fields of machine learning, data mining and natural language processing into practically usable tools and features. The library of algorithms and models within the platform is constantly updated and expanded to ensure that users have access to the latest technologies and methodologies to solve marketing challenges.WiMi’s AutoAIM platform is highly flexible. The platform’s basic frame is based on distributed systems and cloud computing technology, capable of handling large-scale data and complex computing tasks. At the same time, the platform supports integration with various data sources and marketing tools, enabling users to easily import data from existing systems and apply machine learning to actual marketing campaigns.

WiMi has been committed to the development of innovative technologies and is also developing new AI advertising and marketing markets based on its business strengths. Currently, WiMi has developed workflows based on AI and machine learning technologies applied in the field of marketing. WiMi provides marketing professionals with an innovative solution that enables them to easily create, share and reuse workflows for ML projects. The platform talked about in this article provides marketing professionals with powerful tools to implement ML projects and incorporate the benefits of machine learning in their marketing strategies through a visualization-based programming approach. Its technological innovations and capabilities enable marketing professionals to better understand and leverage data for more accurate and personalized campaigns.

WiMi believes that AI and machine learning technologies will play an increasingly important role in marketing, and WiMi will continue to help marketing professionals better meet market challenges and improve the effectiveness and ROI of their marketing campaigns through innovative solutions and platforms. WiMi will also continue to improve and upgrade its platform to meet the market’s needs and users’ expectations, and looks forward to working with more marketing professionals and companies to achieve better marketing results. WiMi will continue to improve and upgrade its platform to meet market needs and users’ expectations, and looks forward to working with more marketing professionals and companies to promote the development of AI in the field of marketing and realize more excellent marketing results.

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