When an organization first embarks on AI model building, many companies are at a loss as to which tool to choose. At first glance, it seems convenient to use AutoML and other AI platforms that have many pre-built models and can build AI models simply by entering data. With an AI platform, the platform compares the accuracy of different models and presents the best model to your organization within hours.

This means that AI models can be built and managed without the need for costly data scientists. While this is true in a way, it misses an important point. Such AI platforms rarely offer scalable, production-grade algorithms worthy of entrusting multi-million dollar enterprise decisions.

There are four important things to consider when choosing which AI to use.

1. A good AI model depends on the data you use. Incomplete, unstructured, or poor quality data will make it difficult to get good results.
2. Tools do not completely replace people. No matter how hard you try, you may not get the ideal training data that your model needs to train effectively. Technical judgment is required regarding the combination of models needed and what adjustments should be made to the training data. Tools are incapable of making these complex decisions, which is why you need a skilled data scientist with both statistical and machine learning skills.
3. There are no two business exactly the same. Different combinations and models are required to meet individual needs and demands. Production deployments require a mix of models to accommodate different business scenarios. AI tools cannot determine these needs. Only a seasoned data scientist can steer you toward your business goals.
4. Continuous monitoring is required even after the model has been successfully deployed. Without monitoring, accuracy will decrease as data changes and grows. A data scientist is needed to analyze and update the model to maintain the same level of accuracy as the initial level.

CrowdANALYTIX (CrowdANALYTIX ) features a combination of pre-built components and customizations by skilled data scientists. We have components for all types of businesses, and we have a community of more than 25,000 data scientists to customize and maintain our clients' models. In addition, business is problematic, so we offer optimized solutions in the form of application programming interfaces (APIs) and applications for the web and mobile. CrowdANALYTIX adjusts model maintenance to maintain model accuracy over time, so the solution grows with the companies that use it.

If you are interested, please feel free to contact us.

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Source:https://www.crowdanalytix.com/how-does-crowdanalytix-differ-from-automl-and-other-ai-platforms/
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