Programming 

Artificial Intelligence, Machine Learning, Deep Learning, and Data Science — What’s the Difference?

Answer: Deep learning is a subarea of machine learning which is a subarea of artificial intelligence. Data science is an interdisciplinary area that combines all of those with math and programming skills to extract useful insights from data. “I’m trying to understand how the area of skills are related to each other, and one is a dependency of another. I hope you clarify for me where to start and how the path looks like. I know it’s a complicated question.” — Barakah, Python Freelancer Course Member Let’s start with a…

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java 

What’s new in Red Hat Dependency Analytics

We are excited to announce a new release of Red Hat Dependency Analytics, a solution that enables developers to create better applications by evaluating and adding high-quality open source components, directly from their IDE. Red Hat Dependency Analytics helps your development team avoid security and licensing issues when building your applications. It plugs into the developer’s IDE, automatically analyzes your software composition, and provides recommendations to address security holes and licensing problems that your team may be missing. Without further ado, let’s jump into the new capabilities offered in this…

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What’s in a Name? Clarifying the Anaconda Metapackage

The name “Anaconda” is overloaded in many ways. There’s our company, Anaconda, Inc., the Anaconda Distribution, the anaconda metapackage, Anaconda Enterprise, and several other, sometimes completely unrelated projects (like Red Hat’s Anaconda). Here we hope… The post What’s in a Name? Clarifying the Anaconda Metapackage appeared first on Anaconda.

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Focus on One Thing. But What’s the Thing?

This article does not give you the standard advice: do what you love. You should love what you do but you don’t necessarily have to do what you love. Oftentimes, the love comes by being successful in a thing. But to be successful, you have to differentiate yourself in the 21st century. In business, it’s all about how much value you can provide to the community. The more value you give, the more successful you’ll become (and the more you’ll love what you do). But it’s about the additional value…

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What’s Faster? COUNT(*) or COUNT(1)?

One of the biggest and undead myths in SQL is that COUNT(*) is faster than COUNT(1). Or was it that COUNT(1) is faster than COUNT(*)? Impossible to remember, because there’s really no reason at all why one should be faster than the other. But is the myth justified? Let’s measure! How does COUNT(…) work? But first, let’s look into some theory. The two ways to count things are not exactly the same thing. Why? COUNT(*) counts all the tuples in a group COUNT(<expr>) counts all the tuples in a group…

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