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Build, Deploy, Scale and Manage AI @ Mosaic AI
Optimize end-to-end life cycle of Machine learning applications by simplifying MLOPs for both Data Scientists and Software/DevOps Engineer
Mosaic AI is a self-served, unified data analytics platform that abstracts the operationalization of the AI lifecycle, behind the scene. All key stakeholders can use this platform to extract business value from the data. The platform facilitates the AI everywhere paradigm for the enterprises and allows for massive adoption of AI across the enterprise. This solution takes care of the deployment, scaling and versioning of AI models, making the data scientists focus on creating AI models without worrying about deployments.
This post intends to give an introduction to Mosaic AI on the following section:
- Introduction to Mosaic AI
Anyone working in the IT industry over a Machine Learning use case, being a Data Scientist, Business Analyst, the IT team responsible for governance and compliance, the business executives or the analytics leaders need to go through a list of complicated and extraneous tasks. These steps may include data preparation, data cleaning, feature engineering, choosing and building the model, setting up the learning environment, training, tuning and debugging the model, managing versions of the models, deploying the model, monitoring the performance of the model, validating the results and eventually scaling for the production environment. A collection of different tools are used at various stages to achieve these complex workflows and it is not so easy to have a seamless development experience from experimentation to live production.
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