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Digital Transformation: Exploring AI

Archives Blogs

Action 8 of the plan specifically speaks to improving data in order to support artificial intelligence (AI) research in federal agencies. Minnesota Mining and Manufacturing) Plant Showing an Employee Working on one of the Products. It emphasizes the need for federal agencies to leverage our data as strategic assets.

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Data monetization: driving the new competitive edge in retail

CGI

Retailers have the opportunity to learn from the expertise of organizations that have built much of their success on data mining. Personalizing the omni-channel customer journey using artificial intelligence is another area where marketers can benefit from the experience of front-runners. Achieving next-level personalization.

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Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. Machine learning (ML) is a subset of artificial intelligence (AI) that focuses on learning from what the data science comes up with. What is machine learning?

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Artificial Intelligence: 6 Step Solution Decomposition Process

Bill Schmarzo - Dell EMC

The conversation is simple because the objective is simple: How do I become more effective at leveraging (big) data and analytics (artificial intelligence) to power my business? Artificial Intelligence Solution Decomposition Process. Figure 1: The Evolution of AI, ML and DL (Source: Nvidia ).

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Leaders need the technical detail

MIKE 2.0

Good examples of changes that are coming with more that is unknown than known include cyber currencies, blockchain, quantum computing, artificial intelligence, smart cities, augmented reality and additive manufacturing. These are some of the technologies that are likely to drive big decisions for leaders in the coming years.

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Artificial Intelligence: 6 Step Solution Decomposition Process

Bill Schmarzo - Dell EMC

The conversation is simple because the objective is simple: How do I become more effective at leveraging (big) data and analytics (artificial intelligence) to power my business? Artificial Intelligence Solution Decomposition Process. Figure 1: The Evolution of AI, ML and DL (Source: Nvidia ).