Strategic investments in AI can be a game-changer. To fulfill the promise of AI, organizations are now tackling skill-set gaps, deployment, and governance processes. In particular, businesses are seeking an alternative where citizen data scientists can quickly get started, and expert data scientists can speed experimentation time from weeks and months to minutes and hours. They need multimodal data science and AI environment where data and analytics specialists collaborate with other experts and optimize model performance end-to-end.

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Get ready to explore how we can help simplify  AI lifecycle management by leveraging AutoAI and other capabilities of Watson Studio and Watson ML to explore, build, deploy and manage models and data while monitoring and improving model accuracy.

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In this session, you will learn how to:

- Predict what's going to happen in your business

- Automate processes and decisions by revealing insights hidden in your data

- Build, deploy, and manage business models that are trusted, transparent, and deployable anywhere

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See how easy simplify the process of experimentation to deployment, speed data exploration, and model development and training, and scale data science operations across the lifecycle.

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