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Data science is the next wave of analytics. TDWI research indicates that the vast majority of organizations realize they need to digitally transform to compete; many organizations are looking to accelerate this change. Data science tools and machine learning frameworks are at the heart of this recent wave.
Although organizational factors—such as supportive leadership, a culture of analytics, the right resources, and organizational models to execute on machine learning—are important for success, there are technology factors that are key as well. On the technology front, machine learning requires the capacity to collect, manage, and access large amounts of accurate and diverse data, the ability to create new features and train models, and the capability to deploy, monitor, and update models in production. Attend this TDWI webinar to learn about six factors for machine learning success.
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