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Data Science Use Cases

Identifying business cases for machine learning driven innovation requires to clearly identify the processes you want to improve or create with an data-driven approach. Machine learning and predictive models can only address clear and well defined questions.

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We constanly benchmark industry best practices and innovative AI-driven use cases to reinforce our knowledge base. We share the insights acquired from these studies with our customers to help them understand the challenges and opportunities that artificial intelligence bring to their industry.

Through our AI use cases white papers serie business managers and data scientists can acquire a first understanding of the business opportunities associated to AI-driven services and identify the key processes and resources required for their implementation.

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Inside this section: [Data Science in Finance]

Technology Stack

ML Cookbooks

Artificial Intelligence isn’t simply a matter of technology. The continual cycle of learning specific to AI need to be carefully understood to analyze the impacts that it will have on AI-related processes, from data management to models management.

Introducing AI-driven operations inside a legacy environment can also be quite challenging from an integration and IT management point of view.

This is why we design machine learning cookbooks that provide predefined ml workflows and reduce the learning curve.

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Inside this section: [API Framework] [Data Science Technological Stacks]