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Working for a company specialized in detecting secrets (if you don’t know what a secret is, please take a moment here and come back), we had to address the question: what would be a good way to categorize secrets?
Take a look at this:
Often, there is a need to compare multiple proportions among samples, wherein proportions can be about product's performance or any other characteristic which can be classified among identifiable categories. Examples of binary classifications can be pass/fail or yes/no.
Just the way equality of central tendencies or variance around them cannot be assumed to be equal, equality of proportions also cannot be assumed to be equal.
The goal of artificial intelligence is to create a machine that can mimic a human mind and to do that, of course, it needs learning capabilities. However, it is more than just about learning. It’s about reasoning, knowledge representation, and even things like abstract thinking.
Machine learning, on the other hand, is solely focused on writing software that can learn from past experiences. One thing you might find astounding is that machine learning is more closely related to data mining and statistics than it is to AI. Why is that? First, we need to know what we mean by machine learning.
Ever struggle with what to write? No worries, we've got you covered. Here's a list of Big Data prompts and article ideas to help cure even the worst cases of writer's block. So, take a moment, check out the prompts below, pick one (or more!), and get to writing.
Also, please feel free to comment on this post to bounce around ideas, ask questions, or share which prompt(s) you're working on.
To speak bluntly, when it comes to its visualization capabilities, Tableau, while it appears so promising, astonishingly lacks in its ability to integrate seamlessly with statistical, hypothesis-driven testing. You may be let down constantly if you feel the need to not only visualize but compare your set of observations between groups on hard statistical grounds.
Hence, one must admit that there is still a strong value gap between visualization tools like Tableau, and pure statistical software such as Minitab, SPSS, SAS, and, of course, the humble yet tremendously powerful and open source workhorse, R.