Practicing data science comes with challenges. It comes with fragmented data, a short supply of data science skills, and various tools, practices, and frameworks to choose from run with rigid IT standards for training and deployment. It's also challenging to operationalize ML models with unclear accuracy and difficult-to-audit predictions.
Using IBM data science tools and solutions, you can accelerate AI-driven innovation with:
- An intelligent data fabric
- A simplified ModelOps lifecycle
- The ability to run any AI model with a flexible deployment
- Trusted and explainable AI
In other words, you get the ability to operationalize data science models on any cloud while instilling trust in AI outcomes. Moreover, you'll be able to manage and govern the AI lifecycle with ModelOps, optimize business decisions with prescriptive analytics and accelerate time to value with visual modeling tools.
Scalable, integrated data science platform with capabilities spanning the full AI and ML lifecycle
Prediction and optimization technologies for better decision-making
Operationalizing AI models in sync with DevOps for faster ROI
Ability to run AI models on premises, in the private cloud or in multiple public clouds
Automate the AI lifecycle and accelerate time to value with an open, flexible architecture.
Collect, organize and analyze data across any cloud with a fully integrated data and AI platform.
Accelerate time to value with this leading visual data science and machine learning tool.
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Discover what you gain from using open source data science on a multicloud data and AI platform.
Learn how high-growth leaders in AI are setting themselves apart in their industries.
See how easily businesses can apply prescriptive analytics using IBM Decision Optimization software.
Learn the definition of data science, its lifecycle and related tools.
Dive deeper and learn in-demand data science skills, build solutions with real sample code, and connect with a global community of developers on IBM Developer.
This guide will help your business navigate the modern predictive analytics landscape, identify opportunities to grow and enhance your use of AI, and empower data science teams and business stakeholders to deliver value quickly.