Companies rely on the cloud for modern app development. Learn the key features that differentiate cloud computing from traditional, on-premises IT architectures.
Source: HOB
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Businesses are using machine learning to improve all the outcomes, by optimizing operational workflows and increasing customer satisfaction.
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As data science has infused across nearly every imaginable field, the work of programmers, analysts, visualization specialists, and myriad other disciplines come together to form modern data science teams tackling society's grand challenges.
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Machine learning and artificial intelligence are growing fields and growing topics of study. While the advanced implementations of machine learning we hear about in the news might sound scary and inaccessible, the core concepts are actually pretty easy to grasp. Here is the list of the most popular resources for machine learning beginners. Some of these books will require familiarity with some coding languages and math, but we'll be sure to mention it when that's the case.
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The age of the smart factory has arrived. Robots, AI and the Internet of Things are taking over processes and machinery, redefining manufacturing and breaking new targets of quality, efficiency, and flexibility
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A world where 2.5 quintillion bytes of data is produced every day a professional who can take all these enormous resources and provide the frameworks for a business solution is indeed a hero. In this module, we are going to talk about how to become a big data engineer before we begin we talk about the role and description.
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Machine learning has been one of the top tech new topics in recent months and is now being widely applied to businesses. Briefly, machine learning (ML) is an application of AI (artificial intelligence) that allows systems to learn and improve without being directly programmed.
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Facebook's commitment to the wider dev community remains as strong as ever if recent developments are any indication.
Source: HOB 2454
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