Automated Modeling

1. What is Automated Modeling? 

Automated machine learning and deep learning collect and process vast amounts of information, quickly analyze it with artificial intelligence, and visualize information. This automated process executes the entire process from data processing to AI modeling and allows it to be deployed by any organization. The automated process automatically fetches relevant information from an appropriate model, making it easier for non-professionals to engage in machine learning and deep learning process for their businesses.

Automated machine learning could be applied to businesses in all industries including manufacturing, finance, insurance, marketing, and management. It enables organizations and companies to make use of their data by helping data scientists and business analysts to build highly accurate AI/ML models and integrate them with production applications. This technology that was only available for large organizations with enormous amount of resources can now be also available for other organizations.

2. Advantages of Automated Modeling

1. Improve efficiency by automatically executing repetitive processes, while allowing data scientists to focus on the actual problems rather than modeling.
2. Automated ML pipelines help avoid potential errors caused by manual operations.
3. Automated machine learning is a big step toward popularizing machine learning, making machine learning available to everyone.


3. Automated Modeling with CLICK AI

CLICK AI provides codeless artificial intelligence model development experience for users. With a just few clicks, users can develop machine learning models at a professional level through the automated process, and can build practical models to maximize business revenues.

- Easily analyze and predict data through automated AI model learning.
- Create new businesses by combining various functions of artificial intelligence.

References
 https://www.unemyr.com/aml-auto-machine-learning-ai/

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